Latest 🤖 Machine Learning Jobs
Browse the most recent job listing for 🤖 Machine Learning Jobs. New roles added daily in Machine Learning Engineer, Data Scientist, AI Research Scientist, Computer Vision Engineer, NLP Engineer, Deep Learning Engineer, Data Engineer, Robotics Engineer, Machine Learning Architect, Business Intelligence Developer
- TView description🌎 Remote📍 ⌛ Posted 1 days ago🌎 Remote📍 \⌛ Posted yesterday
Who we are
At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.
Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.
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Hiring and how we work
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings.
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See yourself at Twilio
Join the team as Twilio’s next Machine Learning Engineer, Customer Memory.
About the job
This position is needed to build and scale the pipelines that turn raw conversation data into structured, searchable customer memory, and the evaluation systems that keep that memory accurate as the product evolves.
You’ll join the Conversation Memory team, which builds the memory layer behind Twilio’s Conversational AI platform: the systems that extract what matters from millions of conversations, resolve it to the right customer, and retrieve it in milliseconds when an agent needs it. Memory that is wrong, stale, or crossed between customers is worse than no memory at all, so quality measurement is a first-class part of the work.
Responsibilities
In this role, you’ll:
- Build the extraction pipeline that turns raw data into structured memory, tuning the LLM prompts and schemas that decide what an AI agent remembers about a customer and what it forgets.
- Own the retrieval path that answers “what do we know about this person?” in milliseconds, working with embeddings, vector search, and ranking
- Contribute to the eval systems that tell us whether memory is actually getting better, turning a fuzzy question of quality into benchmarks and regression gates that run before every change ships.
- Diagnose production issues across the ingestion, extraction, and indexing path using logs, metrics, and traces.
- Partner with Product and ML teams to translate customer problems into system changes and evaluation criteria.
Qualifications
Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn’t followed a traditional path, don’t let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!
Required:
- Experience building backend services, and a demonstrated ability to pick up new languages, frameworks, and tools as the problem demands.
- A curious approach to service management: ability to investigate how systems actually behave in production, and desire to continuously learn how to operate them with rigor and accountability.
- Experience building or working with evaluation/quality-measurement systems, such as regression detection or quality metrics, or the desire to learn.
- Solid grounding in observability practices: structured logging, metrics, and using them to debug distributed systems in production.
- Fluency with AI-assisted dev tools (e.g. agents for code generation, review, debugging), applied with deliberate direction and critical thinking.
Desired:
- Experience with Go and/or Python.
- Experience with event-streaming systems (e.g. Kafka).
- Experience building LLM-backed products.
- Practical experience applying ML, e.g. building, evaluating, or productionizing models.
Location
- This role will be remote, but is not eligible to be hired in San Francisco, CA, Oakland, CA, San Jose, CA, or the surrounding areas.
Travel
We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.
What We Offer
Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.
Compensation
*Please note the salary range information provided applies only to candidates residing in California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State due to local requirements. Compensation for candidates in other locations will be discussed during the hiring process. Please note that hiring for this role is not restricted to the locations listed above.
The estimated pay ranges for this role are as follows:
- Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $128,560 - $160,700
- Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $136,000 - $170,000.
- This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.
The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.
Application deadline information
Applications for this role are intended to be accepted until November 13, but may change based on business needs.
Twilio thinks big. Do you?
We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That’s why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts.
So, if you’re ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn’t what you’re looking for, please consider other open positions.
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Stay alert to recruitment fraud
We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps.
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Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.
View description - by Remote Rocketship🌎 Remote⌛ Posted 17 days ago🌎 Remote⌛ Posted 17d agoJob Description:
- Convert machine learning models, analytical prototypes, and AI solutions into scalable production-ready workflows
- Design, build, and maintain automated data and model pipelines using Python, AWS, Databricks or similar cloud data platforms, Spark, and CI/CD practices
- Develop reusable deployment patterns, templates, documentation, and engineering standards
- Collaborate with Product & Technology, Data Engineering, Cloud Engineering, DevOps, Delivery Platforms, and business operations teams
- Create monitoring frameworks for model performance, data quality, drift, reliability, usage, and business impact
- Support responsible AI and model governance practices, including documentation, auditability, explainability inputs, validation workflows, and model health checks
- Develop feature engineering pipelines, curated data assets, model-serving workflows, and operational data products
- Identify and resolve issues, defects, or process gaps in machine learning pipelines, data workflows, and deployment automation
- Translate operational business needs into technical requirements
- Communicate technical concepts to non-technical stakeholders
- Participate in cross-functional working sessions and provide technical recommendations
- Help drive project execution across Data Science, business, and technology teams
Requirements:
- Bachelor's degree in computer science, data engineering, machine learning engineering, engineering, statistics, mathematics, data science, or another quantitative or technical field
- At least 3 years of relevant experience in machine learning engineering, MLOps, cloud platform engineering, data engineering, software engineering, or similar technical roles
- Experience building production-grade data or machine learning workflows in Python
- Strong background with cloud data technologies, preferably AWS and Databricks, Spark, or similar platforms
- Experience with CI/CD practices, deployment automation, version control, and software engineering fundamentals
- Knowledge of data engineering concepts, including data pipelines, data quality, orchestration, feature engineering, and scalable processing
- Demonstrated ability to partner with data science teams and translate analytical solutions into reliable operational workflows
- Ability to work independently, deliver high-quality work, seek input from others, and contribute to shared standards and best practices
- Strong communication skills, including the ability to explain technical concepts to business stakeholders and non-technical audiences
- Availability five days per week during designated work hours
- Ability to sit at a desk or workstation for extended periods, typically 7–8 hours a day
- Ability to operate a computer, use phone systems, type, and use multiple software programs simultaneously
Benefits:
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- 401(k) match
- Perks supporting employees, their families, and finances
- Career development opportunities
- Quarterly bonus
- Restricted stock unit grant based on individual performance
- Fully remote work from home or location of record within the U.S.
- No in-office requirements
View description - by Remote Rocketship🌎 Remote⌛ Posted 27 days ago🌎 Remote⌛ Posted 27d agoJob Description:
- Architect and implement state-of-the-art pipelines for ad creative generation
- Build systems for product, font, logo, and brand asset preservation using techniques such as IP-Adapters and LoRAs
- Build image and video editing capabilities for smart-cropping, inpainting, outpainting, resizing, and style transfer
- Fine-tune large vision-language models to understand effective ad aesthetics
- Build feedback loops using CTR and CVR metrics to fine-tune generation through RLHF/RLPF for ads
- Engineer filtering and safety systems to prevent non-compliant, unsafe, or copyright-infringing content
- Collaborate with Product, Sales, Policy, UX, and Ads ML teams
- Integrate Ads Creative Effectiveness capabilities into the Ad Manager UI and ad delivery path
- Embed brand-safety filters, copyright checks, and human-in-the-loop escalation paths
Requirements:
- Hands-on experience with tree models, neural nets, ranking, and especially LLM/VLM fine-tuning and RLHF/RLPF for ads
- Comfort with uplift metrics, variance, minimum detectable effects, and experimentation setups for generative systems
- Understanding of auction dynamics and advertiser pain points
- Ability to distill complex ML trade-offs for executives, product managers, and non-technical stakeholders
- Prior work on ad creative tooling, including headline generators, image generators, pre-test models, or advertiser editing flows
- Experience navigating brand-safety, privacy, or copyright frameworks in generative AI products (nice-to-have)
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
- Equity in the form of restricted stock units
- Potential commission, depending on the position offered
- Medical, dental, and vision insurance
- Opportunity to opt out of interview recording, transcription, and summarization
- GView description📍 Sunnyvale, CA⌛ Posted 3 days ago📍 Sunnyvale, CA⌛ Posted 3d ago
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- Experience in Generative AI (Large Language Models, Multi-Modal, Large Vision Models).
- Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing, or other ML disciplines.
Preferred qualifications:
- Master's degree or PhD in Computer Science, or related technical field.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
About the job:
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.In this role, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.Responsibilities:
- Write and test product or system development code.
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
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- CView description - by The SaaS Jobs Board📍 Denver, Colorado, United…⌛ Posted 4 days ago📍 Denver, Colorado, United States; San Francisco, California, United States⌛ Posted 4d ago
About the team/role
We’re hiring an ML Engineer (P3) to build and ship the AI systems that power Checkr’s core products. This role sits on the ML team inside Checkr’s Data & ML organization within Engineering.
Checkr runs millions of background checks a year. The ML team builds the systems that make those checks faster, more accurate, and cheaper to operate: document processing, charge classification, entity resolution, and in-product intelligence. These are production services that Product Engineering depends on daily.
This is not a research role or a notebook role. You’ll own ML services end-to-end: design them, code them, deploy them, monitor them. We need someone who writes production software, builds with LLMs and APIs as first-class tools, and can tell the difference between working code and AI slop. If you’ve spent the last few years building AI-native software and you care deeply about engineering craft, we want to talk.
This role sits in the central Data & ML team within the Engineering organization. You will partner daily with Product Engineering, Product, and cross-functional teams. You’ll also contribute to Checkr’s broader AI strategy, including our initiative to deploy our agentic fleet and build scalable context with our semantic layer.
We are looking for someone based in San Francisco who has built ML systems in fast-moving, impact-first environments. Less process, more shipping. Less paperwork, more results.
What you’ll do
- Build and deploy ML/AI services. Design, develop, and ship ML models and AI systems that Product Engineering teams rely on. You write the model code, the API layer, the monitoring, and the tests. Not notebooks; production services.
- Design with LLMs and APIs. Use LLM APIs (OpenAI, Anthropic, etc.) as building blocks in production systems. You know when to call an LLM, when to fine-tune, when to use a classical model, and when to write a rule. You think about cost, latency, and quality together.
- Ship production software. Write clean, well-structured code with solid OOP, proper abstractions, error handling, and tests. Your code gets reviewed by SWEs and passes. CI/CD is how you work, not something you bolt on at the end.
- Partner with product and engineering. Translate business problems into ML solutions. Define API contracts with product engineers. Explain your approach clearly to non-ML partners and leave the room with alignment, not confusion.
- Evaluate and iterate fast. Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance. Ship and iterate; don’t wait for perfect.
- Ship AI-powered workflows. Put AI to work on your own processes: automate pipelines, build agentic workflows, and contribute reusable skills and context to Checkr’s agentic platform. The expectation is that our teams operate AI-first.
What you bring
- A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience
- 6+ years building software professionally, with at least 2 of those building ML systems that run in production
- Strong Python fluency; you write clean, testable, well-structured code with solid OOP instincts. Hands-on experience using LLM APIs in production systems: prompt engineering, structured outputs, function calling, cost management, and evaluation
- You’ve built and maintained APIs, worked with CI/CD pipelines, and shipped code that other engineers depend on
- Comfort with and enthusiasm for AI-assisted workflows; experience using LLMs, code-generation tools, or agentic systems in production or operational contexts is a strong signal
- You use AI tools (Copilot, Claude, etc.) to move faster, but you understand every line they produce. You can spot AI slop and you don’t ship it
- An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes.
Nice to have
- Experience with MLOps platforms (MLflow, SageMaker, Vertex, or similar)
- Background in document processing, OCR, or information extraction
- Experience with PySpark or large-scale data processing
- Ruby experience (Checkr’s platform runs on Rails)
- Familiarity with compliance-sensitive domains (fintech, legal tech, HR tech)
- Working knowledge of dbt, Snowflake, or modern ELT/data transformation tools
View description - by Remote Rocketship🌎 Remote⌛ Posted 17 days ago🌎 Remote⌛ Posted 17d agoJob Description:
- Design, train, and deploy ML models for text classification, entity extraction, clustering, and narrative and topic detection
- Build and improve LLM-powered features, including prompt design, retrieval-augmented generation (RAG), and agentic workflows
- Develop embedding and semantic-search pipelines to group related content and surface emerging threats
- Productionize models as scalable, monitored services with clear latency, cost, and accuracy targets
- Build evaluation frameworks and datasets to measure model quality, bias, and drift over time
- Work with data engineering to improve ingestion, labeling, and feature pipelines for high-volume, noisy, multilingual text data
- Monitor and retrain models in production, and debug quality issues end to end
- Document approaches and share trade-offs clearly with technical and non-technical stakeholders
- Work closely with data engineers, backend engineers, and product stakeholders as an individual contributor
- Help build an AI-powered risk intelligence platform that enables enterprises to detect, assess, and respond to disinformation, reputational attacks, and security risks
Requirements:
- 4+ years of professional experience building and deploying machine learning models in production
- Strong Python skills and hands-on experience with PyTorch, TensorFlow, or Hugging Face Transformers
- Practical NLP experience, such as classification, named entity recognition (NER), topic modeling, or semantic similarity on real-world text data
- Hands-on experience building with LLMs (OpenAI, Anthropic, or open-source models), including prompt engineering and RAG
- Experience with embeddings and vector search, such as pgvector, Pinecone, OpenSearch, or FAISS
- Experience deploying and operating ML services on AWS, GCP, or Azure, using Docker and CI/CD
- Solid grasp of model evaluation, including metrics, test sets, error analysis, and production monitoring
- Strong communication skills and comfort working in a remote, cross-functional team
- Applicants must be authorized to work for any employer in the U.S.; visa sponsorship is unavailable
- Nice-to-have: experience with trust and safety, threat intelligence, disinformation research, or social media data
- Nice-to-have: experience building agentic AI systems or tool-using LLM workflows, such as LangChain, LlamaIndex, or custom frameworks
- Nice-to-have: experience with multilingual NLP
- Nice-to-have: familiarity with MLOps tooling such as MLflow, SageMaker, Vertex AI, or Weights & Biases
- Nice-to-have: experience with streaming or large-scale data processing, such as Kafka, Spark, or Airflow
- Nice-to-have: experience fine-tuning LLMs with LoRA or PEFT or distilling models to reduce cost and latency
Benefits:
- Equal Opportunity Employer committed to fostering a diverse and inclusive workplace
- Application process accommodations available upon request
View description - by Remote Rocketship🌎 Remote⌛ Posted 18 days ago🌎 Remote⌛ Posted 18d agoJob Description:
- Lead and shape DISCO’s strategic machine learning and AI research initiatives
- Lead impactful machine learning research projects
- Drive innovation in algorithm development and methodologies
- Provide strategic direction for the organization's research agenda
- Optimize research processes, workflows, and resource allocation
- Manage large-scale research programs and oversee multiple projects and teams
- Ensure successful execution of complex research initiatives
- Collaborate with cross-functional teams and external partners
- Engage with industry stakeholders to understand and address real-world challenges
- Drive application of machine learning solutions to create meaningful industry impact
- Develop and execute strategic plans for research initiatives and long-term research strategies
- Participate in the broader research community
- Mentor and guide junior and mid-level researchers
- Lead and manage research teams, fostering knowledge-sharing and innovation
- Contribute to team members’ professional development
Requirements:
- 12 to 15+ years of relevant experience in machine learning research
- Proven track record of impactful research and leadership in large-scale projects
- Demonstrated leadership in driving innovative machine learning research
- Proven ability to lead and guide research teams toward groundbreaking contributions and advancements
- Expertise in developing and executing strategic plans for an organization's overarching machine learning research agenda
- Leadership in fostering a culture of knowledge-sharing and innovation within the research team
- Recognition for external contributions to the broader machine learning research community
- Thought leadership demonstrated through publications, keynote presentations, or participation in industry conferences
- Proven track record of making a significant impact by applying machine learning research to real-world industry problems
- Strong collaboration skills, including effective engagement with industry partners and stakeholders
- Candidates must be legally authorized to work in the United States without sponsorship now or in the future
- DISCO is not currently sponsoring visas, including, but not limited to, H-1B, TN, or EAD, and is not accepting visa transfers
- Operational leadership in optimizing research processes (even better if)
- Extensive experience in program management and overseeing multifaceted initiatives (even better if)
Benefits:
- Benefits, including medical, dental and vision insurance, as well as 401(k)
- Competitive salary plus RSUs
- Flexible PTO
- Opportunity to be a part of a company that is revolutionizing the legal industry
- Growth opportunities throughout the company
- Open, inclusive, and fun environment
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View description - by Remote Rocketship🌎 Remote📍 Remote, District Of…⌛ Posted 19 days ago🌎 Remote📍 Remote, District Of Columbia⌛ Posted 19d agoJob Description:
- Engage with business leaders and teams to understand workflows, challenges, and goals
- Identify AI opportunities and define successful solution outcomes
- Lead cross-functional teams in converting ambiguous opportunities into well-scoped AI initiatives
- Set priorities, technical approaches, success measures, and paths from proof of concept to enterprise adoption
- Architect and build AI proofs of concept using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms
- Own consequential technical work hands-on
- Evaluate feasibility and business value through practical experimentation
- Address data readiness, integration, user experience, security, compliance, performance, cost, and operational needs
- Define scalable architectures and create reusable components, documentation, decision records, and handoff materials
- Provide technical direction for product and platform teams developing successful proofs of concept into enterprise solutions
- Establish engineering standards through technical leadership and mentorship
- Guide design decisions, strengthen delivery practices, and help teams navigate uncertainty
Requirements:
- Doctorate degree and 2 years of Machine Learning Engineer experience; or Master's degree and 6 years of Machine Learning Engineer experience; or Bachelor's degree and 8 years of Machine Learning Engineer experience; or Associate's degree and 10 years of Machine Learning Engineer experience; or High school diploma / GED and 12 years of Machine Learning Engineer experience
- Substantial experience in machine learning and software engineering, including senior technical ownership of applications that progressed beyond a prototype or pilot
- Deep full-stack development skills
- Python proficiency
- Experience developing APIs, application back ends, user interfaces, and data integrations
- Experience with modern software design practices
- Hands-on experience with cloud platforms such as AWS
- DevOps experience including Terraform or similar infrastructure as code, containers, CI/CD, automated deployment, and observability
- Strong practical knowledge of generative AI and machine learning application design
- Experience with model selection, evaluation, inference, and trade-offs among managed services, open-source tools, and custom implementations
- Experience with enterprise architecture and integration patterns
- Knowledge of access controls, secure handling of sensitive data, reliability, performance, and maintainability
- Experience establishing evaluation approaches for AI applications using quantitative and qualitative evidence
- Strong software engineering discipline, including automated testing, version control, modular design, code review, documentation, and AI development tools
- Demonstrated technical leadership through architecture decisions, mentorship, and collaboration across business, product, engineering, security, and platform teams
- At least 2 years of experience directly leading teams, projects, or programs, or directing resource allocation
- Clear written and verbal communication skills
- Experience presenting technical options and trade-offs to technical and business audiences
Benefits:
- A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
- Group medical, dental and vision coverage
- Life and disability insurance
- Flexible spending accounts
- A discretionary annual bonus program
- Stock-based long-term incentives
- Award-winning time-off plans
- Flexible work models where possible
- Career development opportunities
- Work/life balance support
- Financial plans with opportunities to save towards retirement or other goals
View description - by Remote Rocketship🌎 Remote⌛ Posted 27 days ago🌎 Remote⌛ Posted 27d agoJob Description:
- Design, train, and evaluate models for prediction, ranking, and recommendation problems in order management
- Contribute across problem framing, data preparation, feature engineering, training, evaluation, and retraining strategy
- Translate product roadmap priorities into well-framed modeling problems with product management
- Profile customer data, tune and validate models, and work with implementation and solution engineering teams
- Build reproducible Python training pipelines and experiment tracking
- Profile, clean, and validate large-scale enterprise SAP data
- Package models and pipelines for deployment
- Define production monitoring, including drift detection, performance regression signals, and data quality checks
- Translate model behavior and operational reality when production issues arise
- Integrate model output into the product stack through documented service interfaces
- Apply responsible AI practices, including bias evaluation, explainability, and careful data handling
- Document models and explain behavior, limitations, and trade-offs to engineers, delivery teams, sales, and customers
- Review peers' modeling work and raise standards for rigor and reproducibility
Requirements:
- Demonstrated depth in applied machine learning and data science, with models built that reached production and were measured there
- Strong Python skills and fluency with PyTorch or TensorFlow, scikit-learn, pandas, and NumPy
- Solid statistics foundation, including experimental design and appropriate evaluation metrics
- Strong SQL and comfort working with large relational datasets
- Experience building scheduled data and feature pipelines that work with messy source systems
- Experience packaging, documenting, and specifying model requirements for a separate operations or platform team
- Comfort working directly with customers and delivery teams
- TypeScript or JavaScript proficiency sufficient to integrate with the product stack
- Clear written and verbal communication
- Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related technical field, or equivalent practical experience
- Resume must be uploaded in English
Benefits:
- Full-time contractor engagement
- Equal-opportunity and affirmative-action employer
- Equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status
- IView description📍 Mountain View, California⌛ Posted 7 days ago📍 Mountain View, California⌛ Posted 7d ago
About Inworld
Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads.
Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production.
We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA.
Who We're Looking For
A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.
Experience We Find Useful
You don't need all of this. But you need enough to make a case.
Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.
Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding.
High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs.
Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections.
Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups.
Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.
Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.
Who Thrives Here
You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations.
You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem.
You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.
What Working Here Is Like
We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.
We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our Mountain View office.
The base salary range for this full-time position is $250,000 - $300,000+ bonus + equity + benefits.
Inworld Jobs Privacy
- HuddleMate - Answer every question in your next interview or meeting
- RView description📍 Minneapolis, Minnesota⌛ Posted 7 days ago📍 Minneapolis, Minnesota⌛ Posted 7d ago
We are the leading provider of professional services to the middle market globally, our purpose is to instill confidence in a world of change, empowering our clients and people to realize their full potential. Our exceptional people are the key to our unrivaled, culture and talent experience and our ability to be compelling to our clients. You’ll find an environment that inspires and empowers you to thrive both personally and professionally. There’s no one like you and that’s why there’s nowhere like RSM.
The AI Machine Learning Engineer supports the development, testing, and deployment of AI and machine learning solutions that enhance business capabilities. This entry-level role provides hands-on experience working with data and models while building foundational knowledge in AI engineering practices.
ESSENTIAL DUTIES
- Assist in designing, developing, and testing machine learning models for tasks such as classification, regression, clustering, and recommendations.
- Support preprocessing and basic analysis of datasets using standard data tools.
- Work with data scientists, engineers, and product teams to help integrate models into production systems.
- Assist with experiments and model evaluations, documenting results for senior team members.
- Stay up to date with the latest AI/ML research and contribute to team knowledge sharing.
SUCCESSFUL CHARACTERISTICS / SKILLS
Experience & Background
- 1–2 years of experience in machine learning, data science, or software development (internship or academic projects acceptable).
Core Technical Proficiency
- Familiarity with Python and major ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Basic knowledge of data manipulation and visualization tools.
- Broad understanding of machine learning principles and algorithms.
MLOps & Deployment
- Awareness of MLOps practices and tools, such as version control, containerization, or model monitoring.
Advanced Methods
- Foundational understanding of deep learning, natural language processing (NLP), or computer vision concepts.
Professional Traits
- Ability to work independently with guidance and take initiative on assigned tasks.
- Strong analytical and problem-solving skills with eagerness to learn and grow.
- Ability to clearly document and communicate findings.
EDUCATION/CERTIFICATION REQUIREMENTS
- Bachelor’s degree in computer science, data science, engineering, mathematics, or a related field (or equivalent practical experience).
- Azure AI Fundamentals or similar entry-level certification (preferred).
WHAT RSM OFFERS
- Opportunities to develop AI/ML engineering skills in a collaborative environment.
- Mentorship from experienced professionals and exposure to enterprise-level projects.
- Access to training and professional development programs.
- Competitive salary and benefits package.
At RSM, we offer a competitive benefits and compensation package for all our people. Learn more about our total rewards at https://rsmus.com/careers/working-at-rsm/benefits.
We believe flexibility and in-person connection both play an important role in how we work and grow. Most roles at RSM follow a hybrid workstyle, which means team members are aligned to an RSM office and come together in person when it best supports clients, teams, development or relationship-building. Some roles may be virtual or primarily on-site based on role requirements, team priorities and client needs.
All applicants will receive consideration for employment as RSM does not tolerate discrimination and/or harassment based on race; color; creed; sincerely held religious beliefs, practices or observances; sex (including pregnancy or disabilities related to nursing); gender; sexual orientation; HIV Status; national origin; ancestry; familial or marital status; age; physical or mental disability; citizenship; political affiliation; medical condition (including family and medical leave); domestic violence victim status; past, current or prospective service in the US uniformed service; US Military/Veteran status; pre-disposing genetic characteristics or any other characteristic protected under applicable federal, state or local law.
Accommodation for applicants with disabilities is available upon request in connection with the recruitment process and/or employment/partnership. RSM is committed to providing equal opportunity and reasonable accommodation for people with disabilities. If you require a reasonable accommodation to complete an application, interview, or otherwise participate in the recruiting process, please call us at 800-274-3978 or send us an email at [email protected].
RSM does not intend to hire entry level candidates who will require sponsorship now OR in the future (i.e. F-1 visa holders). If you are a recent U.S. college / university graduate possessing 1-2 years of progressive and relevant work experience in a same or similar role to the one for which you are applying, excluding internships, you may be eligible for hire as an experienced associate.
RSM will consider for employment qualified applicants with arrest or conviction records. For those living in California or applying to a position in California, please click here for additional information.
At RSM, an employee’s pay at any point in their career is intended to reflect their experiences, performance, and skills for their current role. The salary range (or starting rate for interns and associates) for this role represents numerous factors considered in the hiring decisions including, but not limited to, education, skills, work experience, certifications, location, etc. As such, pay for the successful candidate(s) could fall anywhere within the stated range.
Compensation Range: $102,800 - $176,000Individuals selected for this role will be eligible for a discretionary bonus based on firm and individual performance.
- FView description📍 Boston, Massachusetts⌛ Posted 8 days ago📍 Boston, Massachusetts⌛ Posted 8d ago
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 167,000 customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We are building state-of-the-art AI and machine learning technologies at Klaviyo to power Composer, as well as personalization products such as smart send time, audience optimization and product recommendations.
As a Senior Machine Learning Platform Engineer, you will help build the core platforms, tools, and infrastructure that ML and AI engineers rely on to create advanced agents and models powering Klaviyo’s products. You will drive key technical initiatives for training and deploying models, unifying and standardizing feature data, and scaling systems that must operate reliably at Klaviyo’s data and traffic scale.
This is a backend-heavy, hands-on technical individual contributor role. You will lead technical execution, conduct code and design reviews, author high-impact code for critical system paths, and collaborate closely with product, ML, data science, and infrastructure partners to deliver durable, high-leverage platforms that accelerate AI development across Klaviyo.
This role is based in Boston.
How You’ll Make an Impact
- Enable AI / ML teams across Klaviyo to ship new models and ML-powered features faster, more safely, and more reliably.
- Evolve our ML and LLM platform architecture so teams can build, evaluate, and operate production ML systems with consistent patterns and best practices.
- Improve reliability, observability, and cost efficiency of ML training, inference, and other ML workloads that serve features like smart send time, audience optimization and product recommendations.
- Raise the bar on engineering and operational excellence for systems that support 167K+ customers and billions of events.
- Architect and scale systems supporting feature storage and real-time retrieval for training and inference datasets
What You’ll Do
- Work closely with AI & ML application teams to design seamless workflows for continuous model training, inference, and monitoring
- Lead technical execution, conduct code and design reviews, and author high-impact code for critical system paths.
- Mentor engineers across the organization, promoting engineering excellence, best practices, and strong design standards.
- Drive architectural design and technical direction for core components of the ML and Feature platforms.
- Partner with product and engineering leaders to define the ML Platform roadmap.
Learn more about the team’s work in our blogs on Ray Jobs & Ray Tune.
Who You Are
We encourage candidates to apply even if they do not meet all the qualifications listed. ML Platform and MLOps are rapidly evolving spaces and we are all constantly learning.
- 7+ years of experience as a software engineer, ML platform engineer, or similar, building backend or distributed systems.
- Demonstrated experience designing and launching AI/ML systems in production at scale
- Strong proficiency in Python (or a similar backend language such as Go, Java, or Scala).
- Experience with cloud infrastructure and platform fundamentals (AWS, kubernetes):
- Familiarity with data-intensive systems: streaming or batch processing, data modeling, and designing systems with large-scale data in mind (spark, ray-data).
- Comfortable collaborating with cross-functional technical partners (ML, product, infra, security).
- Strong communication skills and a track record of driving technical excellence across teams.
What to Expect in Your First 90 Days
30 Days
- Complete Klaviyo boot camp and onboarding for the AI & Analytics organization.
- Build strong context on our AI/ML stack, platform components, and roadmap.
- Meet your team, engineering peers, and key stakeholders across product, ML, infra, and security.
- Onboard to existing technical workstreams and gain familiarity with production ML deployment pipelines.
60 Days
- Deliver high-impact architectural enhancements or core features across the ML Platform end-to-end.
- Conduct deep technical dives into platform architecture and mentor peers through detailed code and design reviews.
- Partner with staff/principal engineers and product leaders to establish technical standards and design patterns for feature platform components.
- Partner with product and technical leaders to shape the next 2–3 quarters of roadmap at a high level.
90 Days
- Own accountability for delivery, reliability, and operational health of key ML Platform systems in your area.
- Have multiple features or platform capabilities shipped that are in active use by ML/AI product teams.
- Participate fully in on-call and incident management for your team’s services.
- Contribute to broader AI/ML strategy and platform direction, influencing how Klaviyo builds and operates models at scale.
Massachusetts Applicants:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.
In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
Base Pay Range For US Locations:$148,000—$222,000 USDThis role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.
Get to Know Klaviyo
We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
IMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non-company email addresses (@klaviyo.com), instant messaging platforms, or unsolicited calls. By clicking "Submit Application" you consent to Klaviyo processing your Personal Data in accordance with our Job Applicant Privacy Notice. If you do not wish for Klaviyo to process your Personal Data, please do not submit an application. You can find our Job Applicant Privacy Notice here and here (FR). - YView description - by EchoJobs🌎 Remote📍 Toronto, Ontario, Canada,⌛ Posted 9 days ago🌎 Remote📍 Toronto, Ontario, Canada,⌛ Posted 9d ago
Senior Machine Learning Engineer - Content and Contributor Intelligence (Remote - CAN) at Yelp
- HuddleMate - Answer every question in your next interview or meeting
- BView description📍 New York, NY⌛ Posted 10 days ago📍 New York, NY⌛ Posted 10d ago
Vice President AI/ML Software Engineer
At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators and champions of inclusion, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.
We are seeking a Vice President AI/ML Software Engineer to design and implement agentic AI systems, RAG pipelines, and intelligent document processing services. This is a senior individual contributor role with high autonomy -- you will own significant components of our AI platform, from embedding pipelines and vector retrieval to multi-agent extraction workflows. You will work closely with the SVP lead to translate architectural vision into production code, while mentoring mid-level engineers and driving technical excellence across the team. This role is in New York, NY
What Sets This Role Apart - You build the agent framework, not just configure one -- custom orchestration engine, not a LangChain wrapper - Production AI with real consequences -- extraction accuracy directly impacts financial operations - Full RAG ownership -- from raw OCR bytes through embedding, retrieval, and generation - Evaluation-driven culture -- golden-truth datasets, automated regression, measurable quality gates - Greenfield AI + enterprise integration -- build new AI-native systems that plug into established platforms
In this role, you'll have the opportunity to impact on our organization in the following ways:
AI Systems Development
Implement agentic pipelines: agent loops, tool registries, memory stores, reasoning traces, and self-correction mechanisms - Build and optimize RAG systems end-to-end: - Document ingestion and preprocessing (OCR output, PDFs, structured/unstructured text) - Chunking strategies (section-aware, semantic, sliding window, hierarchical) - Embedding generation and vector index management - Retrieval orchestration: hybrid search, metadata filtering, re-ranking - Context assembly and prompt construction for downstream LLM calls - Develop vectorization pipelines -- embedding model integration, batch processing, incremental index updates, and similarity search tuning - Implement multi-agent coordination patterns: shared blackboards, inter-agent messaging, task decomposition, and consensus mechanisms - Build prompt engineering infrastructure: template management, few-shot example selection, chain-of-thought scaffolding, and output parsing - Develop evaluation harnesses: automated accuracy measurement, retrieval quality metrics, regression detection, and A/B comparison tooling
Platform & Backend Engineering
Build FastAPI services exposing AI capabilities as production APIs (extraction, validation, classification) - Contribute to Java/Spring Boot platform services where AI integrates with business workflow - Design and maintain database schemas for AI metadata: audit trails, pipeline runs, memory entries, knowledge graphs - Implement content policy enforcement and data governance controls within AI pipelines
Mentorship & Collaboration
Mentor 2-3 mid-level engineers on AI engineering practices - Participate in architecture reviews and design sessions - Document patterns, decisions, and runbooks for AI system operation - Collaborate with product and business stakeholders to translate requirements into technical solutions
To be successful in this role, we’re seeking the following:
Bachelor's degree in Computer Science, Engineering, or related field. - Advanced degree preferred. 6+ years of professional software engineering experience - 2+ years building production AI/ML systems (not just notebooks/prototypes. Strong problem-solving skills with the ability to manage complex data processes. - Excellent collaboration and communication skills to work effectively with cross-functional teams. )
Strong RAG expertise: Embedding models (OpenAI, sentence-transformers, Cohere, or similar) - Vector databases (FAISS, Pinecone, Weaviate, Chroma, pgvector, or similar) - Chunking and retrieval optimization - Context window management and prompt assembly
Agentic AI experience: Agent orchestration (custom frameworks, LangGraph, or similar) - Tool-use patterns, function calling, structured output parsing - Memory and state management for multi-turn agent interactions - Python proficiency (3.11+): FastAPI, async patterns, Pydantic, Poetry, pytest - LLM integration: prompt engineering, token management, streaming, error handling, rate limiting - NLP & document processing: OCR post-processing, text segmentation, entity extraction - Testing rigor: unit tests, integration tests, golden-truth validation, retrieval metric evaluation - API design: RESTful services, OpenAPI specifications, versioning strategies
Preferred Qualifications
Experience with knowledge graph construction from unstructured text - Familiarity with code AI concepts: code generation, automated testing, AI-assisted refactoring - Java/Spring Boot experience for cross-stack contribution - Angular/TypeScript for full-stack context - Experience with model evaluation: F1 scores, precision/recall for extraction, MRR/NDCG for retrieval - Exposure to fine-tuning or prompt optimization techniques - Understanding of graph RAG or hybrid retrieval architectures - Capital markets or financial services domain exposure - Experience with enterprise deployment: Docker, CI/CD, artifact repositories
Technology Stack
AI/Agentic: Multi-agent pipelines, tool-use, autonomous extraction, reasoning loops
RAG: Embedding models, vector stores, hybrid search, chunking, re-ranking
LLM: Azure OpenAI, GPT-4o, structured outputs, function calling
Python: Python 3.12/3.13, FastAPI, Poetry, Pydantic, Gunicorn/Uvicorn
Java: Java 21, Spring Boot 3.x (contributory)
NLP/OCR: Azure Document Intelligence, NLTK, document graph parsing
Database: Oracle, PostgreSQL, vector databases
Infrastructure: Docker, GitLab CI/CD
Testing: Pytest, golden-truth validation, retrieval metrics, evaluation harnesses
Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.At BNY, our culture speaks for itself, check out the latest BNY news at BNY Newsroom & BNY LinkedIn
Here’s a few of our recent awards:
- America’s Most Innovative Companies, Fortune, 2025
- World’s Most Admired Companies, Fortune 2025
- “Most Just Companies”, Just Capital and CNBC, 2025
Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
BNY assesses market data to ensure a competitive compensation package for our employees. The expected base salary for this position when employment commences can be found in the Job Info section at the bottom of the posting.
Base salary offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Base salary is only part of the total rewards package, which may include eligibility for an annual discretionary incentive award. Subject to the terms and conditions of the applicable plans then in effect, eligible employees may enroll in a 401(k) plan as well as participate in Company-sponsored medical, dental, vision, and basic life insurance plans for the employee and the employee’s eligible dependents. Eligible employees also may receive other benefits (including various paid time off benefits, such as vacation and sick time), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, the employee will be in an “at will” position and the Company reserves the right to modify base salary (as well as any other discretionary payments or compensation programs) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
- GView description📍 South San Francisco,…⌛ Posted 10 days ago📍 South San Francisco, California⌛ Posted 10d ago
The Position
We advance science so that we all have more time with the people we love.
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
Within the CoE organization, the Data and Digital Catalyst (DDC) organisation drives the modernisation of our computational and data ecosystems and integration of digital technologies across Research and Early Development to enable our stakeholders, power data-driven science and accelerate decision-making.
The Engineering - AI Enablement group within DDC is accountable for… enabling AI! We do this across the board with our scientific and computational partners based on their goals. We help embed our AI strategy across our research organizations by providing employees with the tools and support needed to adopt AI into our daily work—helping us work smarter and enhancing our day-to-day work. We also build and deploy AI based solutions that reshape and transform business processes in order to unlock value at scale and optimize workflows. We also work on scaling up model training and inference, evaluating the quality of AI/ML models and output, and building impactful applications which accelerate the scientists doing the critical work of drug discovery and development. Partnering with colleagues to build, deploy and evolve a modern tech stack and utilities to enable our AI/ML and agentic efforts will be a key foundation to our success. Our aim is for everyone who can benefit from AI/ML to be able to leverage that utility where and when they need it, from data analysis to literature search to documentation writing. We are aiming for AI/ML to be an everyday utility. The team is cross-functional, impact driven, independent, and constantly evolving to meet the scientific needs.
The Opportunity:
As a machine learning engineer in AI Enablement, you will be working closely with folks that span the gamut from Computational Scientists, Research Scientists, AI/ML experts, Product leaders, DevOps, and everyone in between. You'll build, own, and constantly improve scalable AI/ML based systems that unlock the potential of our diverse scientific data, accelerating the discovery and development of life-changing treatments for patients.
- Design, develop, and test robust, scalable, and maintainable AI/ML facing scientific web applications and backend systems.
- Build tools to evaluate AI/ML model performance and establish new ways to understand AI quality.
- Partner with product managers and scientists to understand user needs, shape requirements, and translate them into actionable technical specifications.
- Develop and maintain systems for collecting, structuring, and storing diverse scientific data that support advanced analytics, machine learning, and other data-driven initiatives.
- Implement, adopt, or evaluate new AI/ML algorithms and analytical techniques
- Contribute to architectural decisions, code reviews, and the evolution of our development processes.
- Be willing to span the stack and contribute where needed, even outside of your core area of expertise.
- Stay up-to-date with emerging technologies and industry best practices and adopt a culture of continuous learning, collaboration, and curiosity.
Who you are:
- Strong proficiency with AI/ML frameworks, libraries, and toolsets.
- Expert knowledge of statistics, machine learning theory, and algorithms.
- Strong knowledge of ML performance optimization, GPU best practices.
- Experience with kubernetes, relational databases, NoSQL databases, or data lakes, and experience working on cloud-native architectures in public clouds (ideally AWS).
- Proven understanding and application of engineering best practices.
- Excellent communication skills and ability to build trusted partnerships with internal and external collaborators.
- Ability to quickly acquire new technologies and programming languages and a passion for continuous learning.
Preferred:
- Experience with biological data (ideally multimodal) and scientific processes.
- Experience working with scientists or in a research environment.
- Experience with workflow automation, GenAI, and/or agents.
Onsite presence on our South San Francisco campus is expected for at least 3 days a week.
Relocation Assistance benefits are not available for this posting.
The expected salary range for this position based on the primary location of San Franscico, CA is $147,600 $274,000. This position is open to both SE5 and SE6 levels, with final leveling to be determined upon completion of the interview process. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.
This position also qualifies for the benefits detailed here:
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
- IView description - by The SaaS Jobs Board📍 Brussel, Belgium⌛ Posted 11 days ago📍 Brussel, Belgium⌛ Posted 11d ago
Company Description
Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.
Job Description
What you will do
As an expert in the field of Machine Learning Engineering you will be responsible for the growth of our Data team, both professionally as well as in size. You will be in charge of shaping and executing the future of your expertise within Sia. You will work on client projects as well as on building our own Sia AI solutions, together with our Dutch team of Data Scientists, our French Data Engineering team, and other business units of Sia Global.Your responsibilities include:
- Leading an internal team towards the development of AI products;
- Working in a multidisciplinary team on client projects as an expert on your subject;
- Making architectural and design decisions for cloud environments;
- Building production level ML/AI solutions with solid software engineering;
- Guiding Data Scientists to scale up their models into production (parallelizing, optimizing, tuning, testing, and wrapping);
- Giving trainings, leading internal meetings and organizing external events;
- Participating in team meetings and workshops with clients;
- Writing blog articles, presenting at conferences and sending out press releases on the subject that you lead.
Who you will work with
The Data Science team is young, diverse and growing (10+). You will join a team that will challenge you and invest in your professional development. We have a flat structure and rely on the entrepreneurial spirit of our members: initiative is highly encouraged. We are striving for well-being, diversity and knowledge-sharing inside the team, so that we can grow together.Who you are
- You are an established technical professional that wants to make the next step in their career, taking on more leadership responsibilities.
- You have first-rate project management and time management skills.
- You are a true problem solver, you turn complex issues into simple and impactful business solutions.
- You are enthusiastic for applying Data Science/Engineering solutions to business problems.
- You have excellent communication skills and can present complicated concepts in a synthetic way.
- You have the ability to adapt rapidly and work on a range of different business areas within a challenging environment.
- You have the ability to work collaboratively in a team environment.
In return, you can expect:
- An international company that gives importance to diversity, inclusion, employee well-being and corporate social responsibilities actions.
- A great working atmosphere with friendly and professional colleagues where innovation and entrepreneurship are encouraged
- A personal development plan with a regular follow-up as well training opportunities to develop yourself
- A competitive salary with great advantages, like mobility budget, hospital insurance, performance -related bonus,...
Qualifications
- MSc level education in Computer Science, Applied Mathematics, Artificial Intelligence, Embedded Systems or related field of study.
- 2-4 years of experience in building production-quality ML/Deep Learning pipelines and models.
- Good understanding of Machine Learning fundamentals and strong knowledge in a specific domain (e.g., Computer Vision, Deep Learning, NLP).
- Expert coding skills in Python and at least one of these languages: Scala, C++, Java.
- Hands-on experience with database management languages (e.g., SQL, PostgreSQL).
- Hands-on experience in cloud-based infrastructures (AWS/GCP/Azure).
- Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes).
- Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks).
- You have a strong interest in data and AI-related topics, the ability to quickly build expertise in these areas, and you’re excited about helping our clients seize the opportunities they offer.
- Experience with coaching/mentoring other engineers.
- Prior experience in Management Consulting is a strong plus.
- Willingness to travel and work at local and international clients.
- Fluency in spoken and written English, French and Dutch is required.
Additional Information
Unfortunately, we are unable to provide a work permit for this position.
Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.
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- IView description - by The SaaS Jobs Board📍 Antwerp, Belgium⌛ Posted 11 days ago📍 Antwerp, Belgium⌛ Posted 11d ago
Company Description
Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.
Job Description
What you will do
As an expert in the field of Machine Learning Engineering you will be responsible for the growth of our Data team, both professionally as well as in size. You will be in charge of shaping and executing the future of your expertise within Sia. You will work on client projects as well as on building our own Sia AI solutions, together with our Dutch team of Data Scientists, our French Data Engineering team, and other business units of Sia Global.Your responsibilities include:
- Leading an internal team towards the development of AI products;
- Working in a multidisciplinary team on client projects as an expert on your subject;
- Making architectural and design decisions for cloud environments;
- Building production level ML/AI solutions with solid software engineering;
- Guiding Data Scientists to scale up their models into production (parallelizing, optimizing, tuning, testing, and wrapping);
- Giving trainings, leading internal meetings and organizing external events;
- Participating in team meetings and workshops with clients;
- Writing blog articles, presenting at conferences and sending out press releases on the subject that you lead.
Who you will work with
The Data Science team is young, diverse and growing (10+). You will join a team that will challenge you and invest in your professional development. We have a flat structure and rely on the entrepreneurial spirit of our members: initiative is highly encouraged. We are striving for well-being, diversity and knowledge-sharing inside the team, so that we can grow together.Who you are
- You are an established technical professional that wants to make the next step in their career, taking on more leadership responsibilities.
- You have first-rate project management and time management skills.
- You are a true problem solver, you turn complex issues into simple and impactful business solutions.
- You are enthusiastic for applying Data Science/Engineering solutions to business problems.
- You have excellent communication skills and can present complicated concepts in a synthetic way.
- You have the ability to adapt rapidly and work on a range of different business areas within a challenging environment.
- You have the ability to work collaboratively in a team environment.
In return, you can expect:
- An international company that gives importance to diversity, inclusion, employee well-being and corporate social responsibilities actions.
- A great working atmosphere with friendly and professional colleagues where innovation and entrepreneurship are encouraged
- A personal development plan with a regular follow-up as well training opportunities to develop yourself
- A competitive salary with great advantages, like mobility budget, hospital insurance, performance -related bonus,...
Qualifications
- MSc level education in Computer Science, Applied Mathematics, Artificial Intelligence, Embedded Systems or related field of study.
- 2-4 years of experience in building production-quality ML/Deep Learning pipelines and models.
- Good understanding of Machine Learning fundamentals and strong knowledge in a specific domain (e.g., Computer Vision, Deep Learning, NLP).
- Expert coding skills in Python and at least one of these languages: Scala, C++, Java.
- Hands-on experience with database management languages (e.g., SQL, PostgreSQL).
- Hands-on experience in cloud-based infrastructures (AWS/GCP/Azure).
- Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes).
- Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks).
- You have a strong interest in data and AI-related topics, the ability to quickly build expertise in these areas, and you’re excited about helping our clients seize the opportunities they offer.
- Experience with coaching/mentoring other engineers.
- Prior experience in Management Consulting is a strong plus.
- Willingness to travel and work at local and international clients.
- Fluency in spoken and written English is required.
- Ability or strong willingness to be professionally proficient in the Dutch language.
Additional Information
We are unable to provide a work permit for this position
Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.
- AView description📍 Office - USA - CA -…⌛ Posted 12 days ago📍 Office - USA - CA - Headquarters, California⌛ Posted 12d ago
Our Mission
At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place.
Who We Are
In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!
We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.Job Summary
Your Career
Palo Alto Networks' ADEM group is seeking an accomplished Principal AI-ML / Data Scientist to serve as a principal technical anchor for our next-generation AIOps platform. In this role, you will bridge the gap between advanced AI research and production-grade backend software engineering, turning massive system telemetry into autonomous, self-healing capabilities.
You will lead the technical design of intelligent, agentic workflows while simultaneously playing a pivotal role in our core backend rearchitecture. This role is ideal for a hands-on technical leader who thrives on building advanced reasoning systems, optimizing large-scale data foundations, and mentoring engineering teams to deliver planet-scale impact.
Your Impact
- Lead the design and implementation of ML/LLM/GenAI-powered agents capable of planning, multi-step execution, self-correction, and seamless collaboration with humans or other agents.
- Build advanced reasoning pipelines, retrieval systems (RAG), and knowledge graph integrations that support autonomous task execution and network troubleshooting.
- Build, fine-tune, or adapt LLMs, multimodal models, and specialized agent models. Successfully integrate traditional AI/ML and statistical models into these agentic workflows to handle complex endpoint telemetry.
- Drive end-to-end solution development from prototype to production, ensuring maximum scalability, reliability, safety, observability, and performance.
- Establish best practices for prompt design, agent memory management, tool usage, and context optimization within the agent ecosystem.
- Continuously evaluate emerging agent frameworks, LLM tooling, and generative AI technologies to inform platform architecture and roadmap decisions.
Qualifications
Your Experience
- 8+ years in software engineering, with a track record of deploying production-grade ML, GenAI, or agentic workflows at scale.
- Strong Python (for AI/ML) combined with professional Go or Java experience for backend microservices.
- Hands-on experience with SQL, designing and restructuring BigQuery schemas, and building/managing scalable data pipelines using Dataflow, Google ADK and GKE
- Solid understanding of retrieval systems (RAG), prompt engineering, model evaluation, and statistical modeling.
- Ability to build platform-level services that integrate cleanly with adjacent ecosystems (e.g., Prisma Access, Cortex).
- BS/MS in Computer Science, Data Science, Engineering, or a related field.
- Knowledge of L3-L7 networking is desirable .
Compensation Disclosure
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
$163,200.00 - $264,000.00/yrOur Commitment
We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together.
We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [email protected].
Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship?: Yes - RView description - by The SaaS Jobs Board🌎 Remote📍 Remote (United States)⌛ Posted 13 days ago🌎 Remote📍 Remote (United States)⌛ Posted 13d ago
Replicant is the industry leader in voice AI for customer service since it was founded in 2017. When you dial the customer service number of one of our customers–like AAA or Fanatics–our bot answers the phone. Over 50% of callers do not even need to talk to a human, and they rate the interaction higher than if they did so. We do this with AI that feels human, scales securely, and delivers real business results. We are backed by top tier Silicon Valley investors and growing rapidly. We are based mostly in the SF Bay Area, Toronto, and New York, and much of our team is distributed throughout other parts of the US and Canada.
Joining Replicant means working on technology that makes customer service both better and cheaper, for a gigantic market of millions of potential customers. We solve huge challenges with a small team, so every improvement you will ship makes a huge difference.
The Machine Learning team empowers enterprise customers and developers on Replicant’s platform to help create delightful conversations that provide fast and effective resolutions to their clients through contact center automation. We define and build the next generation of bot building paradigms for complex enterprise customer service and contact center automation scenarios. You will be part of a cross-functional group of engineers that are applying the latest research in Generative AI and NLP - including LLMs and other advancements in research into our core product lines.
What you'll do
Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields
Translating the latest research into high-performing systems and models that can be practically applied to enhance user experiences
Help set the team's strategic direction, cultivating an environment that encourages innovation and professional growth
Actively engaging in all aspects of development, from ideation and experimentation to implementation and deployment
Collaborating with various teams and product managers to develop and implement ML based solutions, ensuring performance optimization and alignment with broader business goals
What you'll bring
5+ years of software development experience in ML infra, ML tooling, or products with ML usage
Preferred if experienced with the ML ecosystem (e.g. python, pytorch, faiss, elastic search)
Excellent communication skills and a vivid imagination
Passion about engineering and team culture
You love tackling ambiguous technical problems and developing solutions to problems with significant impact
You are an independent thinker and like to own and solve complex problems
You are interested in exploring the nuance and aesthetic of conversations
For all full-time employees, we offer:
🌴 In-person connection that counts: company-wide offsites and smaller team gatherings designed to make remote work feel personal
🖥️ Tech & learning stipend: Conferences, books, courses — interested? We’ll fund them
📍 Remote by design: We’re distributed — no guilt about life events, we trust you to manage your calendar
🏋️ Health & wellness: Flexible vacations, paid sabbatical after 5 years, comprehensive benefits, plus a stipend to support your physical and mental well-being
💸 Compensation that matches your impact: competitive salaries in the company you’re helping to build
📈 Equity with upside: We believe in shared ownership—You’ll own a real piece of a fast-growing AI company
Our Values
Replicant has three core values. It is critical that everyone who joins the team feels excited and moved by these values as every new team member makes an impact on our culture.
Blade Runners: We take ownership and pride to influence the outcomes of our goals. We are successful, and like a Blade Runner, use the tools at our disposal to reach our objectives. We value open and honest communication and proactively seek feedback along the way. We are a company driven to grow and achieve both individually and as a team.
Bread Makers: We are humble and strive toward an egalitarian culture. No task is too big or too small. We work together to achieve our goals and develop our company mission. We believe that the whole is greater than the sum of its parts in everything that we do.
Självdistans (Self-Distance): Självdistans is Swedish for self-distance. It's the ability to critically reflect on oneself and one's relations from an external perspective. With this in mind, we act with objectivity and always remember that we are not our work. There's no perfect science to growing a team or business, but we trust everyone at Replicant to point out our blind spots and humbly admit their own.
Replicant is proud to be an equal opportunity employer. We are committed to fostering an inclusive, diverse and equitable workplace that is built on trust, support and respect. We welcome all individuals and do not discriminate on the basis of gender identity and expression, race, ethnicity, disability, sexual orientation, colour, religion, creed, gender, national origin, age, marital status, pregnancy, sex, citizenship, education, languages spoken or veteran status. Accommodation is available upon request at any point during our recruitment process. If you require an accommodation, please speak to your talent acquisition partner or email us at [email protected] and we’ll work to meet your needs.
- HuddleMate - Answer every question in your next interview or meeting
- TView description🌎 Remote📍 San Francisco, California⌛ Posted 15 days ago🌎 Remote📍 San Francisco, California⌛ Posted 15d ago
About the Role
Join an AI for science team building large-scale models for physical systems. You will develop the infrastructure behind distributed training and inference, helping the team advance models that can predict outcomes and inform effective actions.
What You'll Do
Design, deploy, and maintain distributed machine learning training and inference clusters.
Build scalable end-to-end pipelines for petabyte-scale datasets and model training across the machine learning lifecycle.
Evaluate parallelization methods and numerical precision trade-offs at different model scales.
Profile and debug low-level GPU operations to improve performance.
Track relevant research and apply promising ideas to infrastructure and model workflows.
What We're Looking For
2 to 10 years of experience building large-scale machine learning infrastructure for pretrained or foundation models, including compute, data, inference, and distributed training systems.
Experience optimizing large-scale training, data, or inference workloads, including low-level GPU performance work with CUDA and JAX.
Proficiency with distributed training frameworks such as FSDP or DeepSpeed.
Experience with cloud platforms such as GCP, AWS, or Azure, and with containers and orchestration tools such as Docker and Kubernetes.
Familiarity with scalable model serving, distributed task management, monitoring, logging, observability, and version control practices.
Background in physical AI or AI for science, such as robotics, autonomous systems, or biology, and an interest in working across the machine learning lifecycle.
Comfort working in a fast-paced environment and learning unfamiliar domains.
Compensation & Benefits
Base salary range: $200,000 to $400,000 annually. Visa sponsorship is not available.
Location
Remote within the United States, with San Francisco, California as the primary location.
- SView description📍 Santa Clara, CALIFORNIA⌛ Posted 16 days ago📍 Santa Clara, CALIFORNIA⌛ Posted 16d ago
Company Description
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.
Job Description
What you get to do in this role:
Please note that this role requires you to be in our Santa Clara office for two days per week.About the team - The AI Services Platform Group at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.
We are seeking a Senior Staff Machine Learning Engineer (DevOps) to lead the architecture, optimization, and operational excellence of our AI inference platform. You will own the end-to-end inference lifecycle—from onboarding cutting-edge models to deploying optimized inference engines in production across multiple backends on Kubernetes infrastructure. You'll also architect the intelligent gateway layer using Envoy and ext_proc to enforce access control, provide observability, and enable advanced request routing. This role combines deep technical expertise in GPU compute, LLM APIs, inference frameworks, containerization, orchestration, and API gateway architecture with a bias toward pragmatic engineering and measurable performance impact.
Qualifications
To be successful in this role you have:
- Expertise in Go or Python, OOP, Design Patterns, time and space-efficient algorithms
- Experience building new products that use challenging algorithms
- Expertise in coding efficient, object-oriented, modularized and quality software
- Knowledge of core AI/ML techniques and algorithms
- Knowledge of unit testing, profiling, and code tuning
DevOps: - Deploy, scale, and operate services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines that make releases repeatable and safe to roll back.
- Own observability for what you build — meaningful metrics, useful logs, real tracing, and alerts that fire on customer impact rather than on noise.
- Debug and resolve production incidents independently, participate in on-call, run root-cause analysis, and operate against defined service level objectives.
AI skills
Artificial intelligence strategy is a critical skill at Experienced proficiency for IC5 — it applies to how you build and to what you build.- Confident use of AI coding assistants such as GitHub Copilot or Cursor, paired with the critical eye to review AI-generated code as rigorously as any other — catching logic errors, security anti-patterns, and missed edge cases rather than treating model output as production-ready.
- AI-assisted debugging and trace analysis, and a clear understanding of the data privacy rules governing what goes into a prompt.
Mandatory minimum
- 8+ years of Backend software engineering experience
- 4+ years of designing and operating distributed systems
- 3+ years of Kubernetes in production, including Helm and CI/CD
Bachelor’s degree in computer science, software engineering, or a closely related technical field required.
A master’s degree may offset up to one year of the experience minimum. Equivalent practical experience is considered where technical depth is clearly demonstrable.For positions in this location, we offer a base pay of $201,300 - $352,300, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.
Additional Information
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
- Employee Type: Regular
- Region: AMS - North America and Canada
- Work Persona: Flexible
- SView description📍 Santa Clara, CALIFORNIA⌛ Posted 16 days ago📍 Santa Clara, CALIFORNIA⌛ Posted 16d ago
Company Description
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.
Job Description
What you get to do in this role:
Please note that this role requires you to be in our Santa Clara office for two days per week.About the team - The AI Services Platform Group at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.
We are seeking a Senior Staff Machine Learning Engineer (DevOps) to lead the architecture, optimization, and operational excellence of our AI inference platform. You will own the end-to-end inference lifecycle—from onboarding cutting-edge models to deploying optimized inference engines in production across multiple backends on Kubernetes infrastructure. You'll also architect the intelligent gateway layer using Envoy and ext_proc to enforce access control, provide observability, and enable advanced request routing. This role combines deep technical expertise in GPU compute, LLM APIs, inference frameworks, containerization, orchestration, and API gateway architecture with a bias toward pragmatic engineering and measurable performance impact.
Qualifications
To be successful in this role you have:
- Expertise in Go or Python, OOP, Design Patterns, time and space-efficient algorithms
- Experience building new products that use challenging algorithms
- Expertise in coding efficient, object-oriented, modularized and quality software
- Knowledge of core AI/ML techniques and algorithms
- Knowledge of unit testing, profiling, and code tuning
DevOps: - Deploy, scale, and operate services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines that make releases repeatable and safe to roll back.
- Own observability for what you build — meaningful metrics, useful logs, real tracing, and alerts that fire on customer impact rather than on noise.
- Debug and resolve production incidents independently, participate in on-call, run root-cause analysis, and operate against defined service level objectives.
AI skills
Artificial intelligence strategy is a critical skill at Experienced proficiency for IC5 — it applies to how you build and to what you build.- Confident use of AI coding assistants such as GitHub Copilot or Cursor, paired with the critical eye to review AI-generated code as rigorously as any other — catching logic errors, security anti-patterns, and missed edge cases rather than treating model output as production-ready.
- AI-assisted debugging and trace analysis, and a clear understanding of the data privacy rules governing what goes into a prompt.
Mandatory minimum
- 8+ years of Backend software engineering experience
- 4+ years of designing and operating distributed systems
- 3+ years of Kubernetes in production, including Helm and CI/CD
Bachelor’s degree in computer science, software engineering, or a closely related technical field required.
A master’s degree may offset up to one year of the experience minimum. Equivalent practical experience is considered where technical depth is clearly demonstrable.For positions in this location, we offer a base pay of $201,300 - $352,300, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.
Additional Information
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
- Employee Type: Regular
- Region: AMS - North America and Canada
- Work Persona: Flexible
- HuddleMate - Answer every question in your next interview or meeting
- IView description - by The SaaS Jobs Board📍 Sofia, Bulgaria⌛ Posted 17 days ago📍 Sofia, Bulgaria⌛ Posted 17d ago
Company Description
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.
Job Description
As Associate Machine Learning Scientist you will work on advanced research and development, to enhance relationships with clients, acquire strategic datasets and provide new solutions through product prototyping.
You will concentrate on new data asset evaluation and acquisition and new product prototyping. This will involve inventing and modifying advanced innovative algorithms, and applying them to large datasets to solve difficult business problems. You will balance and prioritise multiple concurrent projects, anticipate obstacles, and make high quality deliveries.
You will report to Director of Data Science and Gen AI.
What you'll do:
- Analyze, evaluate, and document large data sets
- Identify and apply appropriate machine learning/data mining/text mining techniques to uncover the value of the data
- Design data structure and data storage schemes for efficient data manipulation and information retrieval
- Develop tools for data processing and information retrieval
- Develop data-driven models to measure the value of a given data set
- Validate score performance
- Conduct ROI and benefit analysis
- Document and present model process and model performance
- Apply analytical and industry knowledge to construct analytical solutions with details for internal and external clients to solve their business problems.
- Be connected to clients, competitors, relevant market groups, to be aware of and understand movements, trends, up-coming opportunities and risks.
Qualifications
What you'll bring:
- Grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus.
- Understanding of how and when to apply necessary analytical approaches including regression analysis, machine learning, AI, deep learning and other advanced modeling approaches to extract and automate insights from data.
- Grasp of techniques for model cross-validation and penalizing unnecessary complexity, including regularization, Bayesian shrinkage, in-sample vs out-of-sample. Fluency with statistical significance tests and Monte Carlo simulation.
- Experience writing near-production-level code in at least one general purpose programming language (e.g. Python, C++).
- Understanding of Apache family (Hadoop, Spark), latest database technologies (e.g. Graph databases, time-series databases), and natural language processing and other tools for the parsing of unstructured data.
Additional Information
What you'll get:
- Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and book.
- Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
- Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
- Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
- Opportunity for Flexible working hours and Home Office.
Experian is an Equal opportunity employer. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
#LI-Hybrid
Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why. Experian is also proud to be an Equal Opportunity and Affirmative Action employer. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Recruitment Fraud Awareness - Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address. Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.
Experian Careers - Creating a better tomorrow together
Find out what its like to work for Experian by clicking here
- FView description📍 San Mateo, California⌛ Posted 18 days ago📍 San Mateo, California⌛ Posted 18d ago
Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.
At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
ML Platform powers hundreds of use cases and billions of inferences per day across Discovery, Safety, Economy, and Creation. We build the primitives that let teams train, evaluate, deploy, and operate models quickly and safely—so a new ML idea can reach production in weeks or less. We’re looking for a Principal Platform Engineer who treats platform as a product: someone who can turn complex ML/AI infrastructure into clear, durable APIs, SDKs and easy-to-use CLIs/UIs that our internal developers love.
This role blends product thinking, developer experience, backend engineering, and infrastructure at scale. Hands‑on ML experience is a plus; a track record of building internal platforms that developers love is a must.
You Are
- Have 10+ years of professional experience and have a wealth of system design experience upon which to draw to build a scalable, reliable ML platform for all of Roblox.
- A Code Machine; you love not only to design and communicate ideas but also to actually ship product. You obsess about user feedback, and constantly drive towards getting platform features in customers hands.
- Proficient in API design and developer experience—gRPC/REST APIs, SDKs, CLIs, and simple UIs that developers love to use.
- Good to have - experience with the end‑to‑end ML model lifecycle such as model serving, training, model CI/CD, and GPU resources management, and have built ML platform features that are delightful to use.
- You're passionate about infrastructure‑as‑code and automating painful manual processes. You push for platform solutions that don’t leave on-call teams carrying the burden of design choices.
- Passionate about supporting ML engineers to meet and understand their needs, and translating them into clean, durable platform abstractions.
- A clear communicator who excels at both written and verbal communication across differing levels of technical detail.
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a similar technical field.
You Will
- Own platform as a product and set direction end to end: Define requirements, write RFDs, and ship APIs, SDKs, CLIs, and UIs that make ML@Roblox easy to adopt.
- Bootstrap and maintain core ML Platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.
- Set technical strategy and oversee development of high scale and reliable infrastructure systems, with clear SLOs for latency, availability, and cost.
- Design great developer experiences with paved‑road templates, golden paths, opinionated defaults, and clear docs to reduce time‑to‑first‑production.
- Instrument the platform to measure adoption, friction, reliability, and cost; use data to prioritize roadmap and validate outcomes.
- Partner across organizations (ML Engineering, Data Science, Infra/SRE, Security, Finance) to optimize performance, safety, and spend, especially for GPU‑intensive training and high‑QPS inference.
- Propose and implement new platform tooling to improve time to production for MLEs across the full ML lifecycle.
- Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading‑edge technologies and practices.
- Mentor junior and senior engineers, lead design reviews, and drive cross‑team architectural decisions that last.
For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Annual Salary Range$295,250—$345,050 USDRoles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.
- FView description📍 Chantilly, Virginia⌛ Posted 18 days ago📍 Chantilly, Virginia⌛ Posted 18d ago
Active TS/SCI with Polygraph required. U.S. citizenship required.
Location: On-site in Chantilly, VA (Full-Time).
Put AI to work on real mission workflows. You'll train models and integrate pre-trained models into production data flows that automate work for a federal national-security mission.
What you'll do
- Automate workflows and business processes with AI
- - Train models and integrate pre-trained models into data flows
- - Design data structures, data models and software architecture
- - Build in Python, Java and C++ with PyTorch or TensorFlow
- - Build ETL pipelines on AWS
What you bring (required)
- Active TS/SCI with Polygraph
- - PyTorch or TensorFlow
- - Python, Java, C++ and Conda
- - Strong probability, statistics and algorithms
- - Data structures, data modeling and software architecture
- - Training and integrating ML models
Nice to have
- Secure AI on sensitive data
- - Leading AI/ML initiatives
- - ETL pipelines and AWS
- - Hugging Face / LLM experience
Why Falls
A 9% retirement contribution, 100% of family medical premiums paid, and 4 weeks of PTO. We're a small business that's been delivering since 2019, so your work is visible and your voice counts.
Falls Technology is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability, or protected veteran status.
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- PView description🌎 Remote📍 ⌛ Posted 19 days ago🌎 Remote📍 \⌛ Posted 19d ago
PostEra is building an AI-first biotech. We use Proton, our AI platform for medicinal chemistry, to accelerate the discovery of new medicines for patients. PostEra is advancing an internal pipeline focused on Women’s Health and Fertility, and has used Proton to nominate multiple clinical candidates across PMOS and Fertility. PostEra also advances small molecule programs through partnerships with pharma. We’ve closed over $1B in AI partnerships including 4 multi-year agreements with Pfizer and Amgen. PostEra is also leading an antiviral drug discovery center for pandemic preparedness, funded by one of the largest grants in NIH history.
PostEra’s Organizational Structure
We believe time spent navigating complex hierarchies in organizations is better invested in the pursuit of novel technology and scientific discoveries. As such, our organizational structure is intentionally minimalist.
We promote a culture where individual achievement is celebrated through proportional compensation and internal recognition, including meaningful promotions.
Ultimately, our collective focus is delivering cures to patients, which we believe needs a huge amount of cross-disciplinary collaboration, so we’ve fitted our organizational structure to serve that end.
Role Overview
In this role, you will develop the agentic research vertical at PostEra, using agentic systems to automate the development of mechanistic models for biochemical and physiological processes, and analyse biological data for target validation. You will interact closely with chemists and biologists to use these models to drive drug discovery decisions.
You will also develop machine learning methods that can rapidly adapt to new drug discovery problems from limited labeled data. A particular focus is molecular and tabular in-context learning and building foundation models from PostEra’s proprietary multimodal data. You will build models that use the context of drug discovery effectively, determine which prior examples and tasks are relevant, quantify when transfer is helpful or harmful, and provide reliable predictions under distribution shift.
You will help drive the full research loop: defining tasks, constructing datasets and evaluation episodes, developing strong baselines, training and scaling models, performing rigorous ablations, and translating successful methods into capabilities used by PostEra’s scientists. Prior drug discovery experience is not required, but you should be motivated to learn the domain and work closely with medicinal chemists, computational chemists, and other scientists.
Key Responsibilities
Agentic Research for Chemistry and Biology: Develop and benchmark agentic systems to automate the development of quantitative models to simulate biological and physiological processes, and the analysis of biological data.
Research Direction and Execution: Independently identify, formulate, and lead research projects involving in-context learning, agentic systems, few-shot adaptation, tabular foundation models, and molecular machine learning.
In-Context Learning for Molecules: Design and train models that adapt to new assays, endpoints, targets, or chemical series using limited labeled context and heterogeneous historical data.
Benchmarking: Rigorously compare new approaches against strong baselines, curating test cases that deconfounds impact of different sources of bias.
Cross-Functional Collaboration: Work with scientists to connect modeling objectives and evaluation metrics to practical decisions in potency modeling, ADME prediction, selectivity, lead optimization, and the design of early clinical studies.
Model Training and Scaling: Develop efficient training and data pipelines and, where appropriate, scale models across large collections of molecular and tabular tasks.
Research Engineering: Produce readable, reproducible research code; maintain well-tracked experiments; and contribute through code review, documentation, and shared modeling infrastructure.
Scientific Dissemination: Publish results in leading machine learning, medicinal chemistry, or computational biology venues. You will be an ambassador of PostEra to the scientific community.
Key Requirements
PhD degree in machine learning, or STEM research involving the development of novel machine learning approaches
Track record of high-quality research, such as publications and open-source contributions
Strong research or engineering experience in modern machine learning, deep learning, or statistical modeling, backed by understanding of the theory behind machine learning algorithms
Demonstrated expertise in at least one relevant area: agentic workflows for science, machine learning approaches to bioinformatics and clinical data modelling, in-context learning, tabular learning, few-shot learning
Hands-on experience training, debugging, and evaluating ML models in Python using frameworks such as PyTorch or JAX
Ability to independently translate ambiguous scientific or technical problems into well-defined ML projects, including datasets, task definitions, baselines, metrics, and validation schemes
Ability to design careful experiments, benchmarks, and ablations that distinguish improvements from biases, and understand which aspects of the model led to the improvements
Comfort working in a startup environment where priorities evolve, data is imperfect, and high-quality judgment matters as much as raw model complexity
Nice to Haves
Candidates are more likely to succeed in this role if they also have experience with one or more of the following:
Training tabular foundation models, particularly for sparse, heterogeneous, small-data, or high-missingness settings
Developing molecular in-context learning systems or adapting general-purpose in-context models to molecular or scientific data
Large model training, including 1B+ parameter models, distributed training, sharding, data parallelism, model parallelism, and large-scale data pipelines
The development of AI “co-scientist” systems for physical or biological problems
Hands-on experience in modelling biological, biochemical or clinical data using machine learning approaches
Moving research models into production scientific software or computational workflows
Salary: 200k - 300k
Equity: 0.05 - 0.1%
Visa Sponsorship: Not at this time
Hiring Manager: Alpha Lee
Visit us at postera.ai
We use recruiting software to support the hiring process, such as collecting, organizing, and managing applications. Applications are reviewed by our recruiting team, and we do not use artificial intelligence or automated decision-making tools to evaluate candidates or make hiring decisions. Human judgment is used throughout the hiring process, and all final decisions are made by our hiring team. If you would like more information about how your personal data is processed, or about your rights under applicable data protection laws, please contact us.
- QView description🌎 Remote📍 Worldwide⌛ Posted 21 days ago🌎 Remote📍 Worldwide\⌛ Posted 21d ago
[ Quora is a privately held, “remote-first” company . This position can be performed remotely from multiple countries around the world. Please visit careers.quora.com/eligible-countries for details regarding employment eligibility by country.]
About Quora:
Quora’s mission is to grow the world’s collective intelligence. To do so, we have two platforms:
Quora: a global knowledge sharing platform with millions of monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.
Poe: a cloud workspace where millions of users run multiple AI agents on shared context and tools. One subscription, every frontier model, and the collaboration layer that makes them work together.
Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world.
This role will be working on our Quora product.
About the Team and Role:
Our small engineering team works on challenging problems every day. We have a culture that’s rooted in constantly learning and improving, and our engineers are encouraged to think big and experiment with new ideas. As a remote-first company, our engineers have a high degree of flexibility and autonomy. Everyone on the engineering team has a significant impact on our product and our company. We are looking for an experienced machine learning engineer to join our distribution team, working on recommendation systems such as feed, notifications, and Quora’s famous digest emails. At Quora, we use machine learning in almost every part of the product and recommendation systems play an important role in connecting users with content.
As a ranking modeling expert, you will own and advance the second-phase ranking model behind feed and digest, one of the highest-leverage surfaces at Quora, by applying the latest machine learning techniques. You will also play a key role in developing methodologies that our other developers will build on top of.
Responsibilities:
Improve our existing machine learning ranking models using your core coding skills and ML knowledge
Take end-to-end ownership of machine learning systems - data pipelines, candidate extraction, feature engineering, model training, as well as integration into our production systems
Identify new opportunities to apply machine learning to different parts of the Quora product
Work with other machine learning engineers to implement algorithms and systems efficiently
Minimum Requirements:
Availability for meetings and impromptu communication during Quora’s “ coordination hours ” (Mon-Fri: 9am-3pm Pacific Time)
3+ years of professional experience working on recommendation or ranking models
Good understanding of mathematical foundations of machine learning algorithms
Previous experience building end-to-end machine learning systems
Good communication and interpersonal skills
BS, MS, or PhD in Computer Science, Engineering, or a related technical field
Preferred Requirements:
5+ years of experience writing Python or C++ code
Experience with generative recommendation systems
Experience with user behavior or user sequence modeling, transformers, or long sequence modeling applied to ranking
Experience with leading large-scale multi-engineer projects
Flexible and positive team player with outstanding interpersonal skills
Passion for Quora’s mission and goals
At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.
Additional Information:
We are accepting applications on an ongoing basis. This role is a backfill for an existing vacancy.
Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary.
There are many factors that will determine the starting compensation, including but not limited to experience, location, education, and business needs.
US candidates only: For US based applicants, the salary range is $189,507 - $274,604 USD + equity + benefits.
Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 CAD + equity + benefits.
In equity-eligible countries, we currently also offer a flexible equity program where a portion of equity compensation may be taken as cash.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
AI technology may assist in sorting applications and recording interview notes, but all decisions are made by a member of our team.
To ensure a secure hiring process, all final candidates will undergo identity verification and a comprehensive background check prior to onboarding.
Job Applicant Privacy Notice: https://careers.quora.com/quora-global-job-applicant-privacy-notice
#LI-SS2
#LI-REMOTE
- UView description📍 USA-Mountain View,…⌛ Posted 21 days ago📍 USA-Mountain View, California⌛ Posted 21d ago
The opportunity
Unity's ML Engineering Infrastructure team builds the platform that powers machine learning across the company, from feature generation and training data pipelines to distributed training, experimentation, and model serving.
We're looking for a Machine Learning Engineer to help build the platform behind our product intelligence, production ML models, and the teams that develop them. Operating at scale across batch and streaming data, our systems power large-scale training, feature generation, and experimentation. You'll work across the full ML infrastructure stack, from data and feature pipelines to distributed training, orchestration, serving, and observability, going wherever the team needs you most. This role suits someone curious and eager to learn who picks up new tools quickly.
Working closely with your manager and experienced engineers, you'll take on well-scoped projects and deliver them end-to-end using your own judgment, keeping both the day-to-day details and the broader direction of the platform in view.
What you'll be doing
- Build and maintain data and feature pipelines that generate training datasets for machine learning models and experimentation
- Develop and improve infrastructure for distributed training workflows
- Build and operate multi-stage ML pipelines using workflow orchestration tools
- Contribute to model serving and deployment infrastructure, helping models move reliably from training into production
- Improve reproducibility and reliability across the stack through monitoring, alerting, dataset validation, and testing
- Take on projects scoped with your manager and carry them through end-to-end, from design to rollout, using your own judgment along the way
- Investigate uncommon or inconsistent issues across pipelines and training systems, recognize the patterns behind them, and turn them into concrete improvements
- Keep both the hands-on details and the bigger picture in mind, delivering on immediate needs while moving the platform in the right direction
- Partner with ML engineers, researchers, and peers across teams, and share progress and tradeoffs with managers and directors
- Pick up new tools and new parts of the stack as team priorities shift
What we're looking for
- Experience building ML infrastructure, data platforms, or distributed systems in production
- Strong Python skills and experience working with data-intensive workloads
- Hands-on experience with ML frameworks (e.g., PyTorch) and distributed compute (e.g., Ray, Spark)
- Experience with data pipelines, model training workflows, or large datasets beyond academic settings
- Comfortable working across several layers of the ML stack, with a track record of learning new tools and systems quickly
- Ability to spot patterns in ambiguous or inconsistent problems and translate them into practical technical needs
- Clear communication and a collaborative approach with peers, managers, and partner teams
- Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field, or equivalent practical experience
Nice to Have
- Experience with Kubernetes and cloud infrastructure (GCP or AWS)
- Experience with observability tooling (e.g., Prometheus, Grafana)
- Experience with workflow orchestration systems (Airflow, Prefect, etc.)
- Experience with model serving frameworks (e.g., Triton, KServe, Ray Serve)
- Exposure to large-scale data platforms (data lakes, warehouses, streaming systems such as Kafka)
- Familiarity with feature stores or experimentation platforms
Additional Information:
Zone A: $178,700 - $232,300Zone B: $159,100 - $206,800
Zone C: $140,700 - $182,900
This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set.
Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.
Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.
While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program
Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.
Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
This posting is intended to fill an existing vacancy, and we are committed to providing applicants with updates throughout the hiring process in accordance with applicable law.Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.
Your privacy is important to us. Please take a moment to review our Prospect and Applicant Privacy Policies. Should you have any concerns about your privacy, please contact us at [email protected]. - HuddleMate - Answer every question in your next interview or meeting
- RView description📍 Los Angeles, California⌛ Posted 21 days ago📍 Los Angeles, California⌛ Posted 21d ago
As a Staff Machine Learning Engineer on an unpublished R&D game project, you will own the strategy, design, and implementation of ML capabilities. You will work closely with developers, designers, and data scientists to understand their needs, and will be hands-on in conceptualizing, planning, implementing, and maintaining ML-driven solutions. We’re looking for someone who is passionate about enabling great player experiences, thrives in cross-disciplinary collaboration, stays current on the latest ML techniques, and can apply them pragmatically to challenging product problems. You will report to the Engineering Manager within the R&D game project.
Responsibilities:
- Work closely with developers, designers, and data scientists to identify and define improvement opportunities
- Refine modeling and feature strategy for using techniques such as reinforcement learning
- Establish pipeline architecture patterns in partnership with central teams; build reusable training and evaluation pipelines that can be adapted to Riot-wide use cases
- Drive the application of ML/RL systems to improve decision-making and adaptation
- Establish research-to-production practices; balance cutting-edge techniques with production reliability
- Establish evaluation practices in partnership with data scientists and analytics partners; guide experiment design for measuring model impact and set technical evaluation standards
- Define reliability standards in partnership with design and engineering
- Advance and strengthen engineering best practices, including code quality, automated testing, and maintainable architecture
- Mentor engineers and partner disciplines through documentation, reviews, and technical design guidance
- Identify technical risks and bottlenecks, proposing pragmatic solutions to keep projects moving forward
Required Qualifications:
- 6+ years of experience delivering ML systems in production, including 3+ years in applied modeling or ML research roles, ideally within real-time or interactive environments
- Experience with reinforcement learning, including applying RL to practical production problems
- Experience in production environments with interacting models, feedback loops, or systems where model behavior has downstream consequences beyond a single prediction
- Proficiency with modern ML/data science libraries and frameworks such as PyTorch, TensorFlow, pandas, etc.
- Experience collaborating regularly with teammates across multiple disciplines
- Strong communication skills across technical and non-technical audiences
- B.S. in Computer Science or equivalent experience
- Proficiency in Python or similar programming languages
Desired Qualifications:
- Experience with multi-agent reinforcement learning
- Experience in developer tooling
- Experience implementing framework-level UI systems
- Experience in infrastructure and MLOps, such as ML cloud services, containers, and model telemetry
- Experience working in a AAA game engine (e.g. Unity, Unreal)
- Proficiency in C++
For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!
Our Perks:
Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information.
At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.
It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.
Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:
- Safeguarding confidential and sensitive Company data
- Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
- Accessing Company assets, secure digital systems, and networks
- Ensuring a safe interactive environment for players and other Rioters
These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.
- EView description📍 London, England⌛ Posted 21 days ago📍 London, England⌛ Posted 21d ago
WHAT MAKES US EPIC?
At the core of Epic’s success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it’s building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we’re always innovating.
Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development.
PROGRAMMING - SPECIAL PROJECTS
What We Do
The Special Projects team at Epic is responsible for executing high-impact projects that push the envelope to define the future of real-time graphics and gaming technology (The Matrix Awakens, Lumen in the Land of Nanite). In collaboration with the Unreal Engine team, we strive to put our technology and knowledge into the hands of users, empowering developers and content creators with the most powerful suite of real-time tools in the world.
What You'll Do
You will work with our team of applied research programmers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create state-of-the-art tools to support game developers in our ecosystem with a focus on bots (trained gameplay agents, intelligent NPCs, companions, world modeling), as well as automation of a number key areas (including moderation, security, and QA testing). You will be responsible for the design, implementation and deployment of production-ready machine learning models that can be integrated in our ecosystem.
In this role, you will
- Create and deliver production-ready, scalable and high-quality machine learning models and associated algorithms that can make actions in game environments
- Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap
- Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones
What we're looking for
- PhD in Computer Science, Mathematics or related field, or 3+ years of relevant industry experience
- Experience creating / applying machine learning algorithms for action modeling of bots behavior, vision-based or language-instructed, and deploying them as production-level systems in-game
- Expert, hands-on knowledge of:
- Deep learning, incl. but not limited to applications in the gaming industry
- Foundational models and vision and/or language, especially vision-language-action models, reinforcement learning agents, incl. local deployment and model post-training of open weights models
- Reinforcement learning, incl. experience with agentic systems, reward design, policy optimisation, evaluation, and building scalable training environments for agents
- Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch)
- Experience with working collaboratively with other developers, following a flexible/agile/lean approach
This role is open to multiple locations across North America & Europe (including NYC).
Pay Transparency Information
The expected annual base pay range(s) for this position are detailed below. Each base pay range is relevant only for individuals who are residents of or will be expected to work within the specified locale. Compensation varies based on a variety of factors, which include (but aren’t limited to) things such as skills and competencies, qualifications, knowledge, and experience. In addition to base pay, most employees are eligible to participate in Epic’s generous benefit plans and discretionary incentive programs (subject to the terms of those plans or programs).
New York City Base Pay Range$232,666—$341,243 USDABOUT US
Epic Games is a leading interactive entertainment company. For over 30 years we've been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world-class talent.
Like what you hear? Come be a part of something Epic!
Epic Games deeply values diverse teams and an inclusive work culture, and we are proud to be an Equal Opportunity employer. Learn more about our Equal Employment Opportunity (EEO) Policy here.
Note to Recruitment Agencies: Epic does not accept any unsolicited resumes or approaches from any unauthorized third party (including recruitment or placement agencies) (i.e., a third party with whom we do not have a negotiated and validly executed agreement). We will not pay any fees to any unauthorized third party. Further details on these matters can be found here.
- RView description📍 San Mateo, California⌛ Posted 22 days ago📍 San Mateo, California⌛ Posted 22d ago
Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.
At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
At Roblox, we believe advanced research belongs in production, driving core algorithmic advances at a global scale. In this role, you’ll own high-impact projects end-to-end, from initial ideation to production deployment and academic publication, while solving complex, high-dimensional challenges at world-scale concurrency.
Your expertise, across research areas including Computer Vision and Graphics, multimodality, NLP, or recommendation systems, will directly shape the experience for millions of daily active users. Come build the AI-driven infrastructure powering the future of immersive entertainment.
You Will
- Prototype and implement advanced AI and machine learning solutions that drive core platform features and innovation at scale.
- Develop and deploy cutting-edge models (e.g., deep learning, generative AI, multimodal architectures) to solve complex, high-impact technical challenges.
- Collaborate with applied researchers, engineers, and product teams to translate advanced research concepts into production-ready systems.
- Translate complex research into scalable, robust infrastructure that directly impacts hundreds of millions of daily active users.
- Work backward from user and product needs to architecture, and deliver ML solutions that improve platform engagement, safety, and content ecosystem growth.
You Have
- Possess or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.
- Deep expertise and curiosity in a relevant technical domain, such as deep learning, computer vision, NLP, reinforcement learning, or distributed systems.
- Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.
- A strong research track record, evidenced by multiple publications and presentations in rigorous peer-reviewed venues.
You may redact age, date of birth, and dates of attendance/graduation from your resume.
As you apply, you can find more information about our process by signing up for Speak_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.
For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Annual Salary Range$196,750—$243,290 USDRoles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.
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- FView description📍 Sunnyvale, California⌛ Posted 22 days ago📍 Sunnyvale, California⌛ Posted 22d ago
About the Team
DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.
About the Role
You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll work across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability. This role is ideal for an engineer who enjoys pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly.
You’re excited about this opportunity because you will…
- Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company.
- Work on our open-weights serving stack — real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) — alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.
- Design scalable, high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning that power real customer and internal automation use cases
- Push the cost and latency frontier of GPU inference — turning batch jobs that took days into hours and cutting inference cost by multiples — while giving product teams a clean choice across open-weight and closed-source models with reliability, fallback, observability, and cost controls built in.
- Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence.
- Partner closely with ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives.
- Shape the future of DoorDash’s centralized GenAI platform — including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimization, and other post-training and agentic techniques — enabling the next generation of AI-powered products, agents, automation, and personalization.
We’re excited about you because…
- B.S., M.S., or PhD. in Computer Science or equivalent
- 3+ years of industry experience in software engineering
- Strong backend engineering fundamentals, especially in Python and distributed systems.
- Experience building production services, APIs, data pipelines, or ML infrastructure at scale.
- Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization.
- Hands-on experience with LLM inference and/or fine-tuning of open-weight models in production — serving (latency, throughput, batching, autoscaling, GPU utilization) and/or fine-tuning (SFT/DPO/LoRA).
- Ability to work across ambiguous, fast-moving technical areas and turn customer use cases into reusable platform capabilities
- Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software
Nice To Haves
- Experience with LLM inference engines and serving frameworks (e.g., vLLM, SGLang, TensorRT-LLM) in production
- Experience with distributed/multi-node fine-tuning and training pipelines (SFT, DPO/RLHF, LoRA), including data preparation and evaluation
- GPU performance work — multi-node/distributed inference, KV-cache/memory optimization, quantization (FP8/INT8/AWQ/GPTQ), or cold-start/throughput tuning
- Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, serverless/elastic GPU platforms (e.g., Modal), or high-throughput batch systems
- Experience with LLM gateways, model routing, vendor abstraction, or cost attribution
- Experience building developer platforms, internal platforms, or self-serve infrastructure
- Experience building and deploying AI agents or MCP servers in production
- Experience with eval systems, LLM observability, tracing, RAG, search, or vector databases
Compensation
The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.
In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.
DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.
To learn more about our benefits, visit our careers page here.
See below for paid time off details:
- For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
- For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).
About DoorDash
At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods.
DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.
Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.
If you need any accommodations, please inform your recruiting contact upon initial connection.
Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only
We used Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provided Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023. We resumed using Covey Scout for Inbound again on June 29, 2024, and ceased using Covey Scout for Inbound on April 30, 2026.
The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: https://getcovey.com/nyc-local-law-144.
Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash . - IView description🌎 Remote📍 United States⌛ Posted 22 days ago🌎 Remote📍 United States⌛ Posted 22d ago
Principal Machine Learning Operations Engineer
About Us:
BlackSky is a real-time intelligence company. We own and operate the world's most advanced space-based intelligence platform and provide customers satellite imagery, automated analytics and high-frequency monitoring of strategic locations, economic assets and events from around the globe. BlackSky is trusted by the most demanding allied military and intelligence organizations and commercial companies to deliver foresight into critical matters that affect national security and the economy. BlackSky's data enables governments and businesses to see, understand and anticipate change as it happens, giving them the ultimate strategic advantage so they can act quickly. Our global team works with cutting-edge technology to make a difference around the world and prides itself on being people-first, customer-focused and fun.
BlackSky is looking for a Principal AI Engineer, MLOps to pioneer the next generation of space-based intelligence and real-time geospatial analytics. Reporting directly to the Director of Innovative Solutions, you will serve as the technical authority responsible for designing, scaling, deploying, and automating state-of-the-art computer vision (CV) and machine learning (ML) architectures.
In this role, you will bridge the gap between cutting-edge remote sensing research and high-performance, production-ready software. You will lead the charge in utilizing modern AI methodologies to extract actionable intelligence from satellite imagery, optimizing edge and cloud compute environments, and delivering resilient capabilities. While we would strongly prefer candidates near either our Herndon, VA or Seattle, WA offices, we are open to strong remote candidates.
Responsibilities:
- End-to-End Model R&D: Leading full-lifecycle model engineering from initial problem formulation and dataset curation to training, validation, deployment, and error analysis.
- Model Robustness & Domain Adaptation: Driving model resilience against challenging real-world satellite conditions, including off-nadir angles, low light, seasonal variations, weather distortions, dense environments, and cross-sensor domain shifts.
- Production Integration: Ensuring models are reliably trained, versioned, deployed, monitored, and maintained in production.
- Technical Leadership & Strategy: Communicating technical progress, risks, and stack to cross-functional leadership and Product partners while contributing to proposals and white papers.
- Mentorship & Engineering Culture: Providing technical mentorship, spearheading design reviews and experiment planning, and fostering a culture of technical excellence across the engineering team.
- Other job-related duties as assigned.
Required Qualifications:
- Minimum of 12 years of hands-on software engineering experience, including at least four years developing computer vision or machine learning solutions for geospatial, remote sensing, or similarly complex imagery.
- Bachelor’s degree in computer science, engineering, mathematics, or a related quantitative field, or equivalent practical experience.
- Expert-level proficiency in Python and demonstrated experience developing deep learning systems using PyTorch or comparable modern ML frameworks.
- Proven experience designing, training, evaluating, and deploying production-grade computer vision models for tasks such as object detection, segmentation, change detection, image classification, or time-series analysis.
- Strong experience working with remote sensing imagery and the unique challenges associated with geospatial data, including varying spatial resolutions, viewing geometries, sensors, and environmental conditions.
- Hands-on experience building geospatial data and CV pipelines using tools such as Rasterio, GDAL, GeoPandas, Shapely, xarray, Zarr, or similar technologies.
- Demonstrated experience taking CV capabilities from experimentation through production, including model evaluation, deployment, and performance optimization.
- Experience developing and operating ML workloads in AWS, including GPU-based training and inference.
- Strong technical communication skills with the ability to communicate architecture decisions, experimental results, tradeoffs, risks, and recommendations to both technical and non-technical stakeholders.
- Demonstrated ability to provide technical leadership and mentorship across engineering teams without requiring direct management authority.
- The work this role supports requires holding US citizenship.
Preferred Qualifications:
- Master’s degree or Ph.D. in computer science, engineering, mathematics, machine learning, remote sensing, or a related quantitative field.
- At least 15 years of hands-on software engineering, computer vision, or machine learning experience.
- Experience working with imagery from multiple commercial and government remote sensing sources, such as BlackSky, Sentinel, Airbus, Planet, or WorldView.
- Demonstrated experience optimizing ML systems for production constraints, including inference latency, throughput, memory utilization, GPU efficiency, and cost.
- Experience rapidly developing prototypes or proof-of-concept applications and communicating results through customer demonstrations, proposals, white papers, or other technical materials.
- Strong experience with modern MLOps practices, including experiment tracking, dataset and model versioning, reproducibility, automated evaluation, and production monitoring.
- Experience applying foundation models, vision-language models (VLMs), multimodal approaches, or self-supervised learning to geospatial or remote sensing problems.
- Experience adapting models across sensors, geographic regions, resolutions, collection conditions, or other significant domain shifts.
Life at BlackSky for full-time US benefits eligible employees includes:
- Medical, dental, vision, disability, group term life and AD&D, voluntary life and AD&D insurance
- BlackSky pays 100% of employee-only premiums for medical, dental and vision and contributes $100/month for out-of-pocket expenses!
- 15 days of PTO, 11 Company holidays, four Floating Holidays (pro-rated based on hire date), one day of paid volunteerism leave per year, parental leave and more
- 401(k) pre-tax and Roth deferral options with employer match
- Flexible Spending Accounts
- Employee Stock Purchase Program
- Employee Assistance and Travel Assistance Programs
- Employer matching donations
- Professional development
- Mac or PC? Your choice!
- Awesome swag
The anticipated salary range for candidates in Seattle, WA is $185,000-$215,000 per year. The final compensation package offered to a successful candidate will be dependent on specific background and education. BlackSky is a multi-state employer and this pay scale may not reflect salary ranges in other states or locations outside of Seattle, WA.
BlackSky is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity, disability, protected veteran status or any other characteristic protected by law.
To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. #LI-Remote
EEO/ Pay Transparency Statements:
https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf
https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf
- PView description🌎 Remote📍 Seattle, Washington⌛ Posted 22 days ago🌎 Remote📍 Seattle, Washington⌛ Posted 22d ago
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
The User and Content Foundations org is responsible for deeply understanding our content, users and their interactions by generating high-quality, reusable signals and insights that power relevance and personalization across the platform. We work at the intersection of distributed machine learning, large multimodal models, data infrastructure, and product adoption to build foundational capabilities that support our partners, including Discovery, Search, Growth, and Ads. We are looking for an experienced Staff Machine Learning Engineer / Technical Lead who can drive the team’s technical direction, lead the team in building scalable content understanding systems, and make an impact on core Pinterest user and business outcomes. In this role, you will lead ambiguous, high-impact scientific and engineering efforts that create reusable representations, models, and signals. You’ll work across research, machine learning, infrastructure, and engineering domains to turn advances in VLMs, LLMs, multimodal learning and sequence modeling into impact. This role is ideal for a deeply technical leader who combines strong ML judgment with product intuition. Expertise in visual representation learning and content understanding is especially valuable; experience with user understanding, recommender systems and LLMs is also highly relevant.
What will you be doing:
- Set the technical direction and multi-quarter strategy for foundational ML capabilities across visual representation learning, multimodal content understanding, and LLM-based personalization.
- Lead high-impact scientific and technical initiatives from problem definition and research strategy through experimentation, productionization, and adoption.
- Build reusable embeddings, representations, semantic signals, and ML infrastructure while advancing techniques such as VLMs, LLMs, sequence modeling, self-supervised learning, retrieval, and distillation.
- Partner with Product, Data Science, Applied Science, and Engineering to translate foundational capabilities into product outcomes and influence cross-functional roadmaps and investments.
- Establish rigorous practices for modeling, data pipelines, distributed training, inference, evaluation, experimentation, and operational excellence while mentoring engineers and scientists.
What we’re looking for:
- Minimum 7 years of industry experience, including 2+ years of tech leading teams
- MS or PhD degree in computer science, machine learning, or equivalent industry experience.
- Publications at top machine learning, multimodal and/or data mining conferences (e.g., NeurIPS, ICML, CVPR, ECCV, ACL, KDD, SIGIR, etc.) or open-source ML experience
- Hands-on experience with large-scale distributed training of generative models (LLMs, VLMs, sequence models).
- Hands-on experience with distributed tooling for ML data pipelines (e.g. Spark, Hive, MapReduce)
- Hands-on experience leading ambiguous ML and research efforts in building, applying and improving GenAI models for content understanding, search and recommendation systems.
- Technical leadership and experience in setting direction for roadmaps that span modeling, data pipelines and productionization, and aligning stakeholders on priorities, trade-offs, and execution plans.
- Excellent cross-functional communication and collaboration skills
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
- This role will need to be in the office for in-person collaboration 1-2 times/quarter and can be situated anywhere in the USA.
#LI-AK7
#LI-REMOTEAt Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only$189,308—$389,753 USDOur Commitment to Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support. By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire. - HuddleMate - Answer every question in your next interview or meeting
- JView description📍 Jersey City, NJ⌛ Posted 22 days ago📍 Jersey City, NJ⌛ Posted 22d ago
Job Summary
JPMorganChase is hiring top talent to join the growing CIB Technology organization within
Digital & Platform Services / Data Analytics, building production AI agents on NEO that
leverage the firm’s scale, data, and full-service advantage to deliver measurable impact
across the Commercial & Investment Bank and Payments. As a Senior AI Application
Engineer, you’ll design, productionize, and operate LLM-powered agents on NEO (the firm’s
agent runtime PaaS on AWS/Azure), partnering closely with business, product, and
engineering teams in a fast-paced environment.
Core Selling Aspects (Why this role)You’ll build and ship agents that real businesses depend on, not demos. NEO already runs a
federated portfolio of production agents — forecasting, anomaly detection, log analysis,
with sales fulfillment and voice-of-client close behind — and you’ll add to it. You’ll work
across CIB sub-LOBs and Payments, using NEO’s runtime, retrieval, and memory primitives
plus platforms such as Databricks and the GenAI Gateway, and apply MLOps for automation,
continuous delivery, and compliance with AI/ML control expectations.
NEO is the firm’s agent runtime: it gives agents secure execution, agent-to-agent (A2A)
communication, MCP-based tool access, a managed memory layer, and permission-aware,
auditable operation in a regulated environment. Your job is to turn that platform into shipped
agents.
Job Responsibilities- Design and ship production agents on NEO across the federated portfolio, owning them
from prototype through production. - Build retrieval that holds up in production: Graph RAG combining knowledge-graph
traversal with vector search, plus chunking, ranking, and grounding strategies that keep
answers accurate and auditable. - Design agent memory: episodic and semantic memory organized as memory nodes,
with recall, summarization, and decay policies tuned per use case. - Own organizational context management — assembling entitlement-, lineage-, and
tenant-aware context so each agent reasons over only what it’s allowed to see. - Compose multi-agent workflows using A2A, and integrate tools and data through MCP
servers (Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, Splunk). - Build and run evals: task-level and end-to-end agent evaluations, regression suites,
LLM-as-judge, and quality/safety gating before release. - Deploy and operate solutions on public cloud (AWS and/or Azure) with strong SDLC,
security, resiliency, and observability practices.
Partner with product and business partners across CIB and Payments to turn use cases
into shipped, supported agents.
Required Qualifications, Capabilities, and Skills
- MS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or
equivalent experience). - Minimum 7 years of development experience, with at least 4 years working on AI/ML
solutions. - Hands-on experience building LLM-powered or agentic applications in production,
including tracing, evaluations, and guardrails. - Strong programming skills in Python, with deep knowledge of data structures,
algorithms, machine learning, data mining, information retrieval, and statistics. - Practical RAG experience — retrieval quality, embeddings, and vector stores; Graph RAG
a strong plus. - Expert knowledge of at least one of: AWS, Azure, Kubernetes.
Knowledge of data management and data model design; real-time processing using
both SQL (e.g., Postgres) and NoSQL stores (e.g., OpenSearch, Redis). -
Excellent communication skills with the ability to partner effectively with senior technical
and business stakeholders.
Preferred Qualifications, Capabilities, and Skills
- Experience with agent frameworks or runtimes, A2A, or MCP.
Agent memory design (memory nodes, episodic/semantic memory) and organizational
context management. - Knowledge graphs and graph databases used for retrieval.
- Understanding of LLM fine-tuning and small language model inference.
- Ability to develop full-stack products using modern JavaScript/TypeScript frameworks
(e.g., Next.js, Svelte) for agent UIs (AG-UI / NEO UI SDK). - Experience working in the financial or payments domain at a large institution (Investment
Banking, Markets, Securities Services, or adjacent). - Knowledge of high-performance languages such as Go or Rust
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. - Design and ship production agents on NEO across the federated portfolio, owning them
- BView description📍 New York, NY⌛ Posted 24 days ago📍 New York, NY⌛ Posted 24d ago
The AI Garage for Investments & Wealth is seeking a Director, AI / Machine Learning Software Engineer to provide senior technical leadership in establishing and operationalizing enterprise-grade AI Operations (AI Ops) capabilities. This role is critical to ensuring that AI applications, agentic solutions, models, data pipelines, and supporting platforms can be deployed, governed, monitored, and sustained in production with the reliability, security, and operational rigor required in a highly regulated financial services environment.
This leader will serve as the bridge between Engineering and Production, providing oversight across the full AI lifecycle. The role is responsible for defining AI Ops standards, implementing automation and observability frameworks, establishing operational controls, and driving best practices for production support, resiliency, governance, and continuous improvement.
Given the breadth of expertise required across cloud platforms, automation, observability, AI/ML operations, and production reliability, this position requires a senior technical leader with the experience and authority to define strategy, influence architecture decisions, and drive operational excellence across the AI Garage and the broader Wealth & Investment Management Technology organization.
Key Responsibilities- Define and lead the AI Ops strategy for AI Garage for Investments & Wealth.
- Establish standards, frameworks, and best practices for deploying, monitoring, and supporting AI/ML solutions in production.
- Provide technical leadership across the full AI lifecycle, from development through deployment, governance, and ongoing operations.
- Drive automation of AI/ML pipelines, model deployment, monitoring, alerting, and incident response processes.
- Build and enhance observability frameworks to ensure visibility into model performance, data health, system reliability, and operational risks.
- Partner with engineering, platform, infrastructure, data, risk, and production support teams to ensure AI solutions meet enterprise standards for resiliency, security, and compliance.
- Establish operational controls and governance processes for AI applications, models, and data pipelines.
- Lead efforts to improve production reliability, scalability, and efficiency for AI-powered applications and platforms.
- Influence architecture decisions to ensure AI solutions are designed for operational excellence in a regulated environment.
- Drive continuous improvement initiatives, including incident reviews, root cause analysis, and the adoption of lessons learned into engineering and operational practices.
- Mentor and guide senior engineers and technical teams in AI Ops, SRE, and production support best practices.
Required Qualifications- Bachelor’s degree in Computer Science, Engineering, or a related technical field; advanced degree preferred.
- Significant experience in software engineering, machine learning engineering, AI/ML operations, or site reliability engineering.
- Proven experience leading enterprise-scale AI/ML production operations in a highly regulated environment.
- Strong expertise in cloud platforms, distributed systems, automation, CI/CD, and infrastructure as code.
- Experience with observability, monitoring, logging, and alerting frameworks for complex production environments.
- Deep understanding of AI/ML lifecycle management, including model deployment, monitoring, governance, and retraining processes.
- Strong knowledge of production support, incident management, resiliency engineering, and operational controls.
- Demonstrated ability to influence senior stakeholders, architecture decisions, and cross-functional technical strategy.
Excellent communication and leadership skills, with the ability to bridge engineering and production teams effectively.
Preferred Qualifications- Experience within financial services or another highly regulated industry.
- Familiarity with governance, risk, and compliance considerations for AI/ML applications.
- Experience supporting agentic AI solutions, modern ML platforms, and large-scale data pipelines.
- Knowledge of security, reliability, and performance engineering best practices for AI platforms.
Why Join Us
This is an opportunity to play a pivotal leadership role in shaping the AI operational backbone for Investments & Wealth. You will help define how AI solutions are reliably brought into production, managed, and scaled, while influencing enterprise-wide standards and advancing innovation in a critical growth area. - FView description📍 San Mateo, California⌛ Posted 24 days ago📍 San Mateo, California⌛ Posted 24d ago
Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.
At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
ML Platform powers hundreds of use cases and billions of inferences per day across Discovery, Safety, Economy, and Creation. We build the primitives that let teams train, evaluate, deploy, and operate models quickly and safely—so a new ML idea can reach production in weeks or less. We’re looking for a Principal Platform Engineer who treats platform as a product: someone who can turn complex ML/AI infrastructure into clear, durable APIs, SDKs and easy-to-use CLIs/UIs that our internal developers love.
This role blends product thinking, developer experience, backend engineering, and infrastructure at scale. Hands‑on ML experience is a plus; a track record of building internal platforms that developers love is a must.
You Are
- Have 7+ years of professional experience and have a wealth of system design experience upon which to draw to build a scalable, reliable ML platform for all of Roblox.
- A Code Machine; you love not only to design and communicate ideas but also to actually ship product. You obsess about user feedback, and constantly drive towards getting platform features in customers hands.
- Proficient in API design and developer experience—gRPC/REST APIs, SDKs, CLIs, and simple UIs that developers love to use.
- Good to have - experience with the end‑to‑end ML model lifecycle such as model serving, training, model CI/CD, and GPU resources management, and have built ML platform features that are delightful to use.
- You're passionate about infrastructure‑as‑code and automating painful manual processes. You push for platform solutions that don’t leave on-call teams carrying the burden of design choices.
- Passionate about supporting ML engineers to meet and understand their needs, and translating them into clean, durable platform abstractions.
- A clear communicator who excels at both written and verbal communication across differing levels of technical detail.
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a similar technical field.
You Will
- Own platform as a product and set direction end to end: Define requirements, write RFDs, and ship APIs, SDKs, CLIs, and UIs that make ML@Roblox easy to adopt.
- Bootstrap and maintain core ML Platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.
- Set technical strategy and oversee development of high scale and reliable infrastructure systems, with clear SLOs for latency, availability, and cost.
- Design great developer experiences with paved‑road templates, golden paths, opinionated defaults, and clear docs to reduce time‑to‑first‑production.
- Instrument the platform to measure adoption, friction, reliability, and cost; use data to prioritize roadmap and validate outcomes.
- Partner across organizations (ML Engineering, Data Science, Infra/SRE, Security, Finance) to optimize performance, safety, and spend, especially for GPU‑intensive training and high‑QPS inference.
- Propose and implement new platform tooling to improve time to production for MLEs across the full ML lifecycle.
- Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading‑edge technologies and practices.
- Mentor junior and senior engineers, lead design reviews, and drive cross‑team architectural decisions that last.
For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Annual Salary Range$243,290—$312,970 USDRoles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.
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- EView description📍 New York, New York⌛ Posted 24 days ago📍 New York, New York⌛ Posted 24d ago
About the Role
iCapital is seeking an Associate AI Engineer to help build and scale production-grade AI systems that deliver real business outcomes. This role is ideal for an engineer early in their career who enjoys turning ambiguous problem statements into working systems, and who pairs creative problem-solving with disciplined measurement, reproducibility, and operational rigor. This individual will be on the AI/ML team and will work closely with senior AI and machine learning engineers, as well as cross-functional partners, to design, implement, evaluate, and operate AI capabilities as APIs and services in a real-world FinTech environment. This individual will be expected to bring strong analytical fundamentals, curiosity, and a bias toward delivering robust, maintainable systems.
Responsibilities
- Design and implement modular AI capabilities including LLM-based reasoning, document intelligence (OCR/IDP), intelligent knowledge systems, and agentic orchestration to power internal and external workflow automation.
- Own components of the full AI system life cycle to achieve tangible business outcomes, including scoping, POC, solution design, model development, deployment, monitoring and continuous improvement in production environments.
- Build robust evaluation pipelines for AI systems, defining statistically sound, problem-specific metrics, constructing and curating benchmark datasets, and enforcing strict dataset and model versioning to ensure reproducibility and continuous improvement.
- Collaborate across teams and communicate results clearly via documentation, write-ups, and handoffs.
Qualifications
- 2-3 years of relevant experience, including hands-on experience developing production AI/ML systems, including exposure to AWS or cloud-native development patterns for AI/ML workloads, and familiarity with AI development life cycle best practices
- Strong proficiency in Python
- Solid fundamentals in statistics, exploratory data analysis, and the ability to reason about data quality, experiments, and error patterns
- Clear written and verbal communication with the ability to document work and collaborate in a team setting
- Experience with modern LLM tooling (i.e. transformers, unsloth, vLLM, agentic frameworks) or document AI approaches (IDP)
- Familiar with software development best practices (source control, CI/CD, testing, documentation) and working through a full development lifecycle
- Experience with various agentic communication protocols, (i.e. MCP, A2A) is a plus
Benefits
The base salary range for this role is $100,000 to $130,000. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).
We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.
For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/
iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
- SView description📍 Waterford, CT⌛ Posted 24 days ago📍 Waterford, CT⌛ Posted 24d ago
Sonalysts, Inc. is seeking a highly skilled Artificial Intelligence & Machine Learning Systems Engineer with deep expertise in
Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Generative AI, AI agents, and Model Context Protocol.
The ideal candidate should have experience in designing, developing, and optimizing AI-powered applications and workflows with a strong foundation in cybersecurity best practices.
Who are we?
Sonalysts, Inc. is a small, 100% employee-owned business (ESOP) that supports a very diverse set of customers. While the company was originally founded in 1973 with a focus on sonar analysis for the Navy (hence the name), Sonalysts has since expanded into a variety of other Defense and Commercial spaces. With current contracts supporting the Navy, Air Force, Army, and many other customers, Sonalysts leverages the skills and knowledge of its employee owners to help solve the Department of Defense’s most challenging problems while providing the best benefit to our customers. Sonalysts has a diverse and capable workforce comprised of former and retired service members from all branches of the military, and professionals with a wide range of commercial and technical backgrounds. From software development to operations analysis, doctrinal development, engineering, wargaming, targeted knowledge elicitation, or large group facilitation, Sonalysts can meet any challenge.
A small, central corporate structure coupled with a largely de-centralized approach to project management enables Sonalysts to compete with larger Defense Contractors in providing rapid, innovative solutions to meet customer needs while remaining agile and entrepreneurial at heart. Our employee-owners lead and support existing projects while also developing new business and winning new work.
If you are looking to use your technical knowledge to solve challenging problems for the military while benefiting from the flexibility and empowerment of being a contractor or potential future leader in a small business, then Sonalysts may be the place for you.
Key Responsibilities:
- Design and implement scalable LLM-based architectures for AI-powered applications.
- Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for improved model accuracy.
- Work with Generative AI models to enhance automated decision-making systems.
- Integrate and deploy AI models using AI Agents, Model Context Protocol, and retrieval strategies.
- Develop automation workflows using N8N, Pydantic, or other AI workflow tools.
- Optimize and fine-tune AI/ML models for performance and efficiency.
- Utilize GPU acceleration and frameworks like TensorFlow, PyTorch for large-scale AI workloads.
- Implement secure coding practices and cybersecurity protocols in all AI/ML development workflows.
- Ensure secure data handling, model access control, and compliance with data privacy regulations.
- Collaborate with cross-functional teams to integrate AI solutions into production environments.
- Research and implement state-of-the-art advancements in LLMs, multimodal AI, and generative systems.
Required Qualifications & Experience:
- Must be a U.S. citizen, eligible for a U.S. Department of Defense (DoD) SECRET security clearance*
- Bachelor's degree in Computer Science, AI, Machine Learning, Cybersecurity, or a related field.
- 3 or more years of professional experience that includes developing and integrating LLMs, RAG, and Generative AI based solutions.
- Strong problem-solving skills and ability to work in fast-paced, AI-driven environments.
Desired Experience:
- US Navy Combat Systems: Proven experience working with US Navy combat systems, specifically applying systems engineering and software development principles to mission-critical defense environments.
- Containerization & Orchestration: Deep technical proficiency in software containerization technologies, including Docker, Kubernetes, and OpenShift, for the deployment and scaling of complex software architectures.
- Experience with vector databases, knowledge retrieval strategies, and fine-tuning AI models.
- Knowledge of cloud-based AI deployment (AWS, GCP, Azure) with secure infrastructure practices.
- Familiarity with open-source AI tools and frameworks for custom AI solution development.
- Knowledge of compliance standards such as DoD Risk Management Framework (RMF), NIST, and ISO/IEC 27000 series.
- Contributions to AI research, publications, or open-source projects are a plus.
- Strong background in Python, AI frameworks (TensorFlow, PyTorch), and GPU architectures for model training/inference.
- Experience with AI Agent frameworks and Model Context Protocol for scalable AI solutions.
- Hands-on experience with N8N, Pydantic, or other AI workflow tools.
- Demonstrated experience implementing cybersecurity controls in AI environments (e.g., secure APIs, authentication/authorization, encryption).
- Familiarity with threat modeling, vulnerability assessment, and secure deployment of AI models.
- Deep understanding of retrieval systems, knowledge graphs, and multimodal AI applications.
What’s in it for you?
- Opportunity to provide important support to the DoD and to expand your work portfolio to support various projects across the company.
- Opportunity to grow your skillset and pursue project leadership.
- Salary ranges between $85,000-$130,000, dependent on experience, qualifications and other relevant business criteria.
- Becoming an integral part of an innovative employee-owned company which includes:
- Flexible Time Program enabling an optimal work-life balance by permitting partners to arrange their work around personal appointments and vacations, parent-teacher conferences, children’s activities and the like, so long as the partner gets the job done on time.
- Paid Time Off
- 401(k) Plan with company match
- Employee Stock Ownership Plan (ESOP)
- Sales Bonus Program
- Special Performance and Retention Bonus Program
- Health and Preventive Dental Insurance
- Dependent Care Assistance Plan
- Health Care Reimbursement Plan
- Employee Referral Bonus Program
- Professional Development (e.g. Tuition Reimbursement Program, Online Training Program, and Targeted Skills Program)
- Relocation Assistance
*Obtaining a U.S. Government security clearance involves a comprehensive background check. Candidates are eligible for a clearance if they have demonstrated sound financial management (including good credit) over time, are free of criminal records, have limited foreign contacts or ties, and other factors indicative of a position of trust to protect information sensitive to the U.S. Government.
Sonalysts, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against on the basis of, race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a protected veteran, disability, or other basis protected by law.
This job is not available to residents of New York City because of local law restrictions there.
Drug Testing Employer
www.sonalysts.com
- FView description📍 Spring, Texas⌛ Posted 24 days ago📍 Spring, Texas⌛ Posted 24d agoSenior Machine Learning Platform Engineer — Model Hosting & MLOps
Description -
Role summary
We are hiring a Senior Machine Learning Platform Engineer to build the infrastructure and engineering workflows that take custom models from development into reliable production use. This is a hands-on role for someone who has hosted LLMs on GPU infrastructure, developed the cloud platform around model serving, and built MLOps pipelines that make releases repeatable and observable.
You will work with model developers, application engineers, security, and cloud platform teams to turn a model artifact into a secure, scalable inference service. The work spans serving architecture, infrastructure as code, deployment automation, model lifecycle management, and production operations across AWS and Azure, with potential integration into on-premises environments. You will also help shape agent workflows that use hosted models, so serving choices support the needs of multi-step applications. Success means teams can deploy, update, monitor, and troubleshoot models through clear, reusable platform patterns.
What you will do
- Design and build hosting for custom ML and AI models across AWS and Azure, with particular focus on GPU-backed LLM inference and real-time endpoints; support batch inference where appropriate.
- Package models and their dependencies into reproducible serving workloads; choose and implement suitable managed services, containers, or Kubernetes-based patterns based on throughput, latency, security, reliability, and cost.
- Provision and configure Kubernetes clusters or other suitable hosting infrastructure, including compute, storage, API access, identity and access controls, secrets, networking integration, observability, and environment configuration.
- Help design secure connections and deployment patterns between cloud and on-premises environments as hosting needs evolve.
- Develop infrastructure as code and deployment automation so model-hosting environments can be provisioned, reviewed, promoted, and maintained consistently.
- Build MLOps workflows for model registration, versioning, validation, release, rollback, and retirement. Connect training or model preparation to deployment through automated pipelines and appropriate quality gates.
- Partner with application teams to design and prototype agent workflows, including model and tool orchestration, state handling, failure recovery, and evaluation.
- Translate agent workload patterns into hosting decisions about model selection, context length, concurrency, latency, cost, tool access, and end-to-end tracing.
- Establish production monitoring for service health, latency, throughput, errors, GPU and other resource use, and model behavior. Share responsibility for diagnosing incidents and improving capacity, reliability, and cost.
- Create reusable deployment templates, reference architectures, documentation, and onboarding paths that help other teams ship models safely.
- Partner with model and application teams on practical tradeoffs such as online versus batch inference, managed versus self-hosted serving, scaling, evaluation, data handling, and operational ownership.
Required experience
- Hands-on experience hosting LLM inference on GPU infrastructure in a production environment. You can explain what you personally built, how models reached production, and how you managed throughput, latency, utilization, reliability, and cost.
- Experience building the surrounding model-serving platform for custom models, such as inference runtimes, deployment patterns, endpoint access, scaling, and operational tooling.
- Strong software engineering skills, especially Python, with experience building services, automation, and maintainable production code.
- Experience developing infrastructure for ML workloads across AWS and Azure, with deep hands-on delivery in at least one and practical ability to work in the other. You have used infrastructure as code such as Terraform or an equivalent tool.
- Experience provisioning, configuring, and maintaining Kubernetes or another production hosting platform for containerized inference workloads.
- Experience building or operating ML deployment pipelines with versioned artifacts, automated validation, CI/CD, environment promotion, and rollback.
- Familiarity with LLM agent patterns, including model invocation, tool calls, and multi-step workflows, and how they affect serving capacity, reliability, and access controls.
- Working knowledge of production concerns for inference services: scaling, latency, availability, logging and metrics, shared incident response, access control, and cost.
- Ability to work across model development, application, platform, and security teams; turn ambiguous requirements into a working design; and document the resulting operational approach.
Helpful experience
- Advanced GPU inference optimization, including capacity planning, batching, autoscaling, memory use, model loading, and performance tuning.
- Serving generative or other compute-intensive custom models beyond LLMs; selecting and tuning inference servers and runtime configurations.
- AWS SageMaker or EKS; Azure Machine Learning or AKS; or equivalent managed and self-hosted model platforms.
- Hybrid or on-premises model hosting, including connectivity, security boundaries, hardware constraints, and operational handoff.
- Model registries, experiment tracking, data or feature pipelines, scheduled retraining, model evaluation, and drift or quality monitoring.
- Secure enterprise deployment patterns such as private networking, IAM/RBAC, secrets management, auditability, and handling sensitive data.
- Building shared ML platform capabilities or self-service workflows used by multiple engineering teams.
- Hands-on development of agent workflows, including tool integration, evaluation, tracing, or guardrails.
Who will thrive here
You are an engineer who has taken responsibility for what happens after a model is trained: how it is packaged, deployed, secured, scaled, observed, updated, and supported. You are comfortable writing code and infrastructure, investigating production failures, and making clear tradeoffs with partner teams.
Pay & Benefits
The pay range for this role is $147,050 to $230,850 USD annually with additional
opportunities for pay in the form of bonus and/or equity (applies to United
States of America candidates only). Pay varies by work location, job-related
knowledge, skills, and experience.
Benefits:
HP offers a comprehensive benefits package for this position, including:
- Health insurance
- Dental insurance
- Vision insurance
- Long term/short term disability insurance
- Employee assistance program
- Flexible spending account
- Life insurance
- Generous time off policies, including;
- 4-12 weeks fully paid parental leave based on tenure
- 11 paid holidays
- Additional flexible paid vacation and sick leave
- US benefits overview https://hpbenefits.ce.alight.com/
The compensation and benefits information is accurate as of the date of this
posting. The Company reserves the right to modify this information at any time,
with or without notice, subject to applicable law.
Job -
SoftwareSchedule -
Full timeShift -
No shift premium (United States of America)Travel -
NoRelocation -
NoEqual Opportunity Employer (EEO) -
HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).
Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.
For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal"
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- SView description🌎 Remote📍 Remote, Texas⌛ Posted 25 days ago🌎 Remote📍 Remote, Texas⌛ Posted 25d ago
“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” — Dr. Jim Rebesco, Cofounder and CEO, Striveworks
The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.
Striveworks was built to solve that problem.
What you’ll build
Since 2018, we have delivered the most trusted AI systems operating in real-world use cases—providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.
As a Senior Machine Learning Engineer, Agentic Systems, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working directly with customers, data scientists, software engineers, and DevOps engineers, you’ll develop machine learning solutions, orchestrate complex data and agentic workflows, and help shape the capabilities of Chariot, our proprietary AI operations platform. You’ll work across models, agents, tools, and workflows to build reliable and effective AI systems while analyzing and improving their performance and usability. Your work will inform platform improvements, expand our capabilities, and extend to the field through mission-critical deployments, direct customer contact, and insights that shape what we build next.
What it’s like here
We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership—because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.
What we’re looking for
- A BS degree in computer science, machine learning, or a related discipline and 6+ years relevant experience
- Demonstrated experience delivering data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
- Experience designing, building, evaluating, and optimizing LLM-powered agents and agentic workflows
- Experience integrating AI systems with external tools, APIs, MCP servers, and enterprise data sources
- Experience developing evaluation approaches and frameworks to measure agent performance, reliability, and safety
- Familiarity with retrieval-augmented generation (RAG), tool use, planning, and multi-agent architectures
- Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
- Strong software engineering fundamentals—including algorithms, data structures, and design patterns—as well as proficiency in at least one systems programming language (e.g., Go, Rust, C++, Java, Scala)
- Proficiency with modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
- Active Secret (or above) US security clearance and US citizenship
The following isn’t required, but we’d love to see it:
- An advanced degree in data science, machine learning, computer science, or a related discipline
- Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
- Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [K8s], infrastructure as code, major cloud architectures)
- Experience with a variety of unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, telemetry signals)
- Experience defining, scoping, planning, and delivering complex technical solutions
- Experience leading a small team
- Experience delivering technology solutions in secure government environments
This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 20% of the time.
Compensation
The anticipated base pay range for this position is $185,000–$230,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.
Benefits include:
- Medical/dental/vision insurance
- Voluntary life, long-term disability, accident, and hospital indemnity insurance
- HSA and FSA (including dependent care FSA) plans
- 401(k) plan
- Unlimited PTO
- Paid parental leave
Ready to build systems that work for a mission that matters? Let’s talk.
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact People Operations at [email protected].
In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.
Striveworks is a participating employer in the E-Verify program.
- BView description📍 Washington, District Of…⌛ Posted 25 days ago📍 Washington, District Of Columbia⌛ Posted 25d ago
Job Description
Remote Work: Hybrid Job Number: R0241162 Location: Washington,DC,US Additional Locations:- Alexandria, Virginia, USA
- Annapolis Junction, Maryland, USA
- Arlington, Virginia, USA
- McLean, Virginia, USA
The Opportunity:
As an experienced machine learning engineer, you understand good software is more than just a good user experience. To compete in today’s technical landscape, mission-oriented machine learning solutions must be architected, designed, and built to handle fast-moving data, to seamlessly scale with infrastructure based on system usage, and to expand based on evolving mission requirements. We’re looking for an engineer like you to create artificial intelligence (AI) and machine learning (ML) enabled solutions that help solve our toughest challenges facing the Defense and Intelligence sectors.
On our team, you’ll design, create, and implement complete AI systems that will transform client operations, increase data accessibility, and optimize AI and ML systems. You’ll ensure that your team’s solutions consider the broader ecosystem and operating environment as well as future functionality and enhancements. Additionally, you’ll deepen your skill set in areas like software engineering, machine learning operations (MLOps), and software deployment and integration into a variety of different mission environments.
Ready to transform the Defense and Intelligence sectors with software systems to aid data accessibility and AI and ML operationalization?
Join us. The world can’t wait.
You Have:
3+ years of experience as a ML engineer and building production-grade ML solutions, including work involving LLMs, agents, or complex automation frameworks
3+ years of experience working within data science or data research in a professional or academic environment, and training or deploying models across multiple modalities of data
3+ years of experience working in cloud environments, including AWS and Azure
2+ years of experience deploying and integrating production-grade ML models using tools, such as Docker and Kubernetes
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex
Experience in connecting Agents to APIs, Cloud platforms, or databases
Experience evaluating LLM performance and building observation layers for stakeholders, including Grafana, Langfuse, LangSmith, or Phoenix
Experience evaluating architectural tradeoffs and designing robust service-based software applications for scalable use
Ability to obtain a Secret clearance
Bachelor’s degree
Nice If You Have:
Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and vLLM
Experience with client engagements, client-facing project work, and business development
Experience with project work in deep learning, computer vision, NLP, or signal processing
Experience deploying and managing data brokering solutions, including Kafka, Red Panda, Confluent, and other related services
Ability to adapt in a rapidly changing environment
Possession of excellent verbal and written communication skills
Possession of excellent interpersonal, analytical, problem-solving, and organizational skills
Secret clearance
Master's degree
Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.- Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
- Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen or customer facility, in alignment with your leadership's expectations and the needs of the role.
- Onsite: If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
About Us
Booz Allen is an advanced technology company. We build commercial-grade products and solutions for America’s most critical defense, civil, and national security priorities.
Applicants who need a reasonable accommodation for any part of the application, hiring, or employment process because of a disability, a sincerely held religious belief, practice, or observance, or as otherwise required by applicable law should contact the Booz Allen Help Desk by calling 1-877-927-8278 or sending an email to [email protected]. We will review requests on an individualized basis and provide reasonable accommodations consistent with applicable law.
- TView description📍 Templecombe, England⌛ Posted 25 days ago📍 Templecombe, England⌛ Posted 25d agoLocation: Templecombe, United Kingdom
Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services.
2027 Machine Learning Apprentice - Level 6 AI Engineer
Start Date: 06 September 2027
Salary: £24,000 per annum
Employee type: Permanent
Location: Templecombe
Working Schedule: Monday – Friday, 37 hours a week (8 hours Monday – Thursday, 5 hours Friday)
Turn your curiosity into a career. If you're passionate about engineering, eager to learn, and looking for a degree apprenticeship that combines academic study with exciting on-the-job experience, we'd love to hear from you.
Benefits of the programme:
- Earn a salary while studying for your qualification
- Gain hands-on experience in a real engineering environment
- Receive job-specific training and development
- Achieve a recognised engineering qualification
- Secure a permanent role from the start of your apprenticeship
- Have your tuition fees fully paid
About the Role
As a Machine Learning Apprentice, you will develop the technical knowledge, practical skills and professional behaviours needed to become a confident and capable engineer.
Working as part of our Specialist Underwater Systems Engineering team, you will support the rapid delivery of novel solutions, ensuring that our Royal Navy and export customers have the capability needed in today’s fast paced environment to carry out their critical missions, keeping them and our nation safe and secure.
Your responsibilities may include:
- Working with Underwater Systems specialists and software developers to create novel solutions
- Developing solutions with our partners across the multinational Thales organisation, academia and industry
- Participating in testing and validation activities
- Assisting with engineering investigations and problem solving
- Visiting customer sites, platforms and installations to support surveys, trials and system deployment where required
- Working with experienced engineers on live projects
What You Will Learn
Throughout the apprenticeship, you will gain experience and knowledge in:
- Professional engineering behaviours and industry best practice
- Understanding and working with complex engineering systems
- Different engineering roles and activities across live projects
- The Systems Engineering Lifecycle and key engineering processes
- Requirements capture, requirements management and system design techniques
- Systems Engineering tools and methods
- Testing, integration, verification, validation and qualification (IVVQ) activities
- Structured and methodical approaches to problem solving and investigation
Apprenticeship Programme
You will study towards a Level 6 in AI Engineer Apprenticeship with QA. The AI Engineer programme gives you the skills to design, build, and deploy advanced AI systems - including generative AI and deep learning. You’ll move from concept to real-world application. Creating solutions that scale and deliver impact.
The programme is 23 months in duration and is delivered via a virtual delivery model combining:
- Instructor led live workshops (28 days)
- Interactive labs and self-paced learning
Programme structure - You will complete learning in:
- AI System Development and Automation
- AI Solution Design and Testing
- Deep Learning and Transformers
- Business Process Optimisation with AI
- Security, Ethics and Explainable AI
- Leading AI and Future Innovation
On completion of the programme, you will have the opportunity to achieve the Microsoft Certified: Azure AI Engineer Associate (AI -102) in addition to the IfATE L6AIE Qualification.
Entry Requirements
To apply, you will need:
A Levels
- Three A Levels Grade B or above in Maths
- At least one other relevant subject (Physics, Computer Science, Software, ICT)
- Or Level 4/5 apprenticeship in a relevant discipline
GCSEs
- Minimum of five GCSEs at Grade 9-4 (A-C) English and Maths
Please note that Computer Science graduates are not eligible due to funding restrictions.
Benefits
· Competitive salary of £24,000 per annum
· Performance-related pay uplifts
· Holiday entitlement of 201 hours a year (plus a company day and bank holidays)
· Contributory Company Pension
· Health Care Cash Plan
· Hybrid/flexible working options
· Employee assistance programme
· Learning and development support
· Employee discounts and wellbeing initiatives
· Life Cover
· 80 Hours Volunteering per year (first two years)
Thales Apprentice Recruitment Process
1. Apply Online - submit your application online to register your interest. You only need to register for one role as you will have the opportunity to apply for additional roles at the full application stage.
2. Upload Your CV
3. Check your emails for the invitation to apply – this will come from [email protected]
4. Complete Your Application – follow the link provided in the email to complete your application. You can apply for one primary role and up to 3 additional roles.
5. Complete Online Tests - undertake the online assessments designed to evaluate your suitability for the role.
6. Virtual Assessment Centre - candidates who progress from the online assessment stage will attend a virtual assessment centre, which will include group exercises, and competency-based interviews.
7. Job Offer – successful candidates who perform well throughout the recruitment process will receive a job offer from Thales.
For further information about our Future Talent recruitment process, including hints and tips, or to connect with a member of the Future Talent Team, a Graduate, or an Apprentice, please visit Thales Future Talent - Connectr.
Please note, assessment centres for shortlisted candidates will be held between February - May 2027. Induction week for all Graduate and Apprentices will take place from Monday 6 September - Friday 10 September 2027.
Closing date: Our applications will close at 11.59pm on Wednesday 17 February 2027, this is the only time we will be accepting applications this year. Please note, we will be in contact by the end of February 2027 with details of next steps.
PLEASE NOTE THAT ROLES MAY CLOSE EARLIER THAN THE ADVERTISED DEADLINE IF WE RECEIVE A HIGH NUMER OF APPLICATIONS. WE ENCOURAGE YOU TO APPLY AS SOON AS POSSIBLE TO AVOID MISSING OUT ON THIS OPPORTUNITY.
Because of the work we do at Thales, all roles are subject to security requirements.
To be considered for this position, you must have the permanent right to work in the UK and be able to successfully complete and maintain UK Government security checks, including Baseline Personnel Security Standard (BPSS) screening and Security Clearance (SC), which is a government background check, before starting employment.
To be eligible for SC clearance, you will typically need to have lived in the UK continuously for the last five years. As part of the vetting process, you will be asked to provide evidence of your identity, right to work in the UK, any time spent overseas during the last five years, and your employment and/or education history.
In addition, this role supports a UK Eyes Only programme and is therefore subject to government-mandated nationality restrictions. To satisfy the security clearance requirements for access to highly sensitive information, applicants must have been British citizens from birth and must not hold any other nationality. This requirement is determined by the UK Government and is a condition of programme access rather than an employment preference.
For further details of the evidence required to apply for security clearance please follow this link - https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels/national-security-vetting-clearance-levels.
Thales is an equal opportunities employer and diversity, and inclusion are integral to the success of Thales.
At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here.
We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here.
If this role isn’t quite right for you, we encourage you to join our talent community where your details will be shared with our recruitment teams for other potential opportunities. Join the Talent Community here.
Join Thales in the UK – Innovate with us and shape the future!
- JobCopilot - Get 10x more Job Interviews
- TView description📍 Manor Royal Crawley,…⌛ Posted 25 days ago📍 Manor Royal Crawley, England⌛ Posted 25d agoLocation: Crawley, United Kingdom
Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services.
2027 AI Engineer Apprentice - Level 6 Machine Learning
Start Date: 06 September 2027
Salary: £24,000 per annum
Employee type: Permanent
Location: Crawley
Working Schedule: Monday – Friday, 37 hours a week (8 hours Monday – Thursday, 5 hours Friday)
Turn your curiosity into a career. If you're passionate about artificial intelligence, eager to learn, and looking for a degree apprenticeship that combines academic study with exciting on-the-job experience, we'd love to hear from you.
Benefits of the programme:
- Earn a salary while studying for your qualification
- Gain hands-on experience in a real AI and engineering environment
- Receive job-specific training and development
- Achieve a recognised Level 6 qualification
- Secure a permanent role from the start of your apprenticeship
- Have your tuition fees fully paid
About the Role
As an AI Engineer Apprentice, you will develop the technical knowledge, practical skills and professional behaviours needed to design, build, test and deploy dependable AI-enabled solutions.
Working as part of our AI and engineering community, you will contribute to live projects across the machine learning lifecycle, collaborating with software, data, systems and domain specialists to turn needs into secure, maintainable solutions.
Your responsibilities may include:
- Preparing, exploring and validating data for machine learning use cases
- Developing and evaluating machine learning models and AI-enabled software components
- Writing clean, tested and documented code using appropriate engineering tools and practices
- Supporting model integration, deployment, monitoring and performance improvement
- Contributing to technical reviews, experiments and structured problem solving
- Working with experienced engineers and researchers on live projects
What You Will Learn
Throughout the apprenticeship, you will gain experience and knowledge in:
- Professional engineering behaviours, teamwork and industry best practice
- Programming, software engineering, version control and automated testing
- Data preparation, feature engineering and data quality techniques
- Machine learning methods, model selection, training and evaluation
- Deployment patterns, MLOps, monitoring and lifecycle management
- Cloud, compute and development tools used to deliver AI solutions
- Responsible AI, security, privacy, safety and regulatory considerations
- Structured approaches to troubleshooting, experimentation and continuous improvement
Apprenticeship Programme
You will study towards a Level 6 AI Engineer apprenticeship with QA, developing the knowledge, skills and behaviours required to build and apply artificial intelligence responsibly in an engineering environment.
The programme is delivered through a virtual learning model, combining:
- Live virtual lectures (28 days)
- Online learning resources
- Self-directed study
This programme will take you through the AI lifecycle, from design and build, through to deployment and governance – providing a strong foundation for your role within Thales. The programme includes the Microsoft certified Azure AI Engineer Associate qualification, in addition to the Level 6 Machine Learning Engineer Apprenticeship qualification.
Entry Requirements
To apply, you will need:
A Levels
- Three A Levels Grade B or above in Maths
- At least one relevant subject (Physics, Computer Science, Software, ICT)
- Or a Level 4/5 apprenticeship in a similar subject
GCSEs
- Minimum of five GCSEs at Grade 9-4 (A-C), including English and Maths
Please note Computer Science graduates are not eligible due to funding restrictions.
Benefits
- Competitive salary of £24,000 per annum
- Performance-related pay uplifts
- Holiday entitlement of 201 hours a year (plus a company day and bank holidays)
- Contributory Company Pension
- Health Care Cash Plan
- Hybrid/flexible working options
- Employee assistance programme
- Learning and development support
- Employee discounts and wellbeing initiatives
- Life Cover
- 80 Hours Volunteering per year (first two years)
Thales Apprentice Recruitment Process
1. Apply Online - submit your application online to register your interest. You only need to register for one role as you will have the opportunity to apply for additional roles at the full application stage.
2. Upload Your CV
3. Check your emails for the invitation to apply – this will come from [email protected]
4. Complete Your Application – follow the link provided in the email to complete your application. You can apply for one primary role and up to 3 additional roles.
5. Complete Online Tests - undertake the online assessments designed to evaluate your suitability for the role.
6. Virtual Assessment Centre - candidates who progress from the online assessment stage will attend a virtual assessment centre, which will include group exercises, and competency-based interviews.
7. Job Offer – successful candidates who perform well throughout the recruitment process will receive a job offer from Thales.
For further information about our Future Talent recruitment process, including hints and tips, or to connect with a member of the Future Talent Team, a Graduate, or an Apprentice, please visit Thales Future Talent - Connectr.
Please note, assessment centres for shortlisted candidates will be held between February - May 2027. Induction week for all Graduate and Apprentices will take place from Monday 6 September - Friday 10 September 2027.
Closing date: Our applications will close at 11.59pm on Wednesday 17 February 2027, this is the only time we will be accepting applications this year. Please note, we will be in contact by the end of February 2027 with details of next steps.
PLEASE NOTE THAT ROLES MAY CLOSE EARLIER THAN THE ADVERTISED DEADLINE IF WE RECEIVE A HIGH NUMER OF APPLICATIONS. WE ENCOURAGE YOU TO APPLY AS SOON AS POSSIBLE TO AVOID MISSING OUT ON THIS OPPORTUNITY.
Because of the work we do at Thales, all roles are subject to security requirements.
To be considered for this position, you must have the permanent right to work in the UK and be able to successfully complete and maintain UK Government security checks, including Baseline Personnel Security Standard (BPSS) screening and Security Clearance (SC), which is a government background check, before starting employment.
To be eligible for SC clearance, you will typically need to have lived in the UK continuously for the last five years. As part of the vetting process, you will be asked to provide evidence of your identity, right to work in the UK, any time spent overseas during the last five years, and your employment and/or education history.
For further details of the evidence required to apply for security clearance please follow this link - https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels/national-security-vetting-clearance-levels.
Thales is an equal opportunities employer and diversity, and inclusion are integral to the success of Thales.
At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here.
We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here.
If this role isn’t quite right for you, we encourage you to join our talent community where your details will be shared with our recruitment teams for other potential opportunities. Join the Talent Community here.
Join Thales in the UK – Innovate with us and shape the future!
- SView description📍 Santa Clara, CALIFORNIA⌛ Posted 25 days ago📍 Santa Clara, CALIFORNIA⌛ Posted 25d ago
Company Description
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.
Job Description
What you get to do in this role:
The Advanced Technology Group (ATG) at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.
You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.
- Build the best cloud-based AI/ML solutions to power intelligent enterprise services
- Collaborate daily with a team of like-minded developers, product managers and quality engineers to produce quality software
- Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality solutions to our users
Qualifications
To be successful in this role you have:
- Expertise in Go or Python, Design Patterns, time and space-efficient algorithms
- Experience building new products that use challenging algorithms
- Expertise in coding efficient, object-oriented, modularized and quality software
- Knowledge of core AI/ML techniques and algorithms
- Knowledge of unit testing, profiling, and code tuning
DevOps requirements
- Deploy, scale, and operate services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines that make releases repeatable and safe to roll back.
- Own observability for what you build — meaningful metrics, useful logs, real tracing, and alerts that fire on customer impact rather than on noise.
- Debug and resolve production incidents independently, participate in on-call, run root-cause analysis, and operate against defined service level objectives
Desired skills but not required:
- Confident use of AI coding assistants such as GitHub Copilot or Cursor, paired with the critical eye to review AI-generated code as rigorously as any other — catching logic errors, security anti-patterns, and missed edge cases rather than treating model output as production-ready.
- AI-assisted debugging and trace analysis, and a clear understanding of the data privacy rules governing what goes into a prompt.
For positions in this location, we offer a base pay of $161,300 - $274,200, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.
Additional Information
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
- Employee Type: Regular
- Region: AMS - North America and Canada
- Work Persona: Flexible
- SView description🌎 Remote📍 Remote, Texas⌛ Posted 25 days ago🌎 Remote📍 Remote, Texas⌛ Posted 25d ago
“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” — Dr. Jim Rebesco, Cofounder and CEO, Striveworks
The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.
Striveworks was built to solve that problem.
What you’ll build
Since 2018, we have delivered the most trusted AI systems operating in real-world use cases—providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.
As a Senior Machine Learning Engineer, Agentic Systems, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working directly with customers, data scientists, software engineers, and DevOps engineers, you’ll develop machine learning solutions, orchestrate complex data and agentic workflows, and help shape the capabilities of Chariot, our proprietary AI operations platform. You’ll work across models, agents, tools, and workflows to build reliable and effective AI systems while analyzing and improving their performance and usability. Your work will inform platform improvements, expand our capabilities, and extend to the field through mission-critical deployments, direct customer contact, and insights that shape what we build next.
What it’s like here
We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership—because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.
What we’re looking for
- A BS degree in computer science, machine learning, or a related discipline and 6+ years relevant experience
- Demonstrated experience delivering data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
- Experience designing, building, evaluating, and optimizing LLM-powered agents and agentic workflows
- Experience integrating AI systems with external tools, APIs, MCP servers, and enterprise data sources
- Experience developing evaluation approaches and frameworks to measure agent performance, reliability, and safety
- Familiarity with retrieval-augmented generation (RAG), tool use, planning, and multi-agent architectures
- Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
- Strong software engineering fundamentals, including algorithms, data structures, design patterns, proficiency in at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
- Proficiency with modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
- US citizenship with eligibility and willingness to obtain and maintain a Secret US security clearance
The following isn’t required, but we’d love to see it:
- An advanced degree in data science, machine learning, computer science, or a related discipline
- Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
- Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [K8s], infrastructure as code, major cloud architectures)
- Experience with a variety of unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, telemetry signals)
- Experience defining, scoping, planning, and delivering complex technical solutions
- Experience leading a small team
- Experience delivering technology solutions in secure government environments
- Active Secret (or above) US security clearance
This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 20% of the time.
Compensation
The anticipated base pay range for this position is $160,000–$200,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.
Benefits include:
- Medical/dental/vision insurance
- Voluntary life, long-term disability, accident, and hospital indemnity insurance
- HSA and FSA (including dependent care FSA) plans
- 401(k) plan
- Unlimited PTO
- Paid parental leave
Ready to build systems that work for a mission that matters? Let’s talk.
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact People Operations at [email protected].
In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.
Striveworks is a participating employer in the E-Verify program.
- HuddleMate - Answer every question in your next interview or meeting
- RView description🌎 Remote📍 ⌛ Posted 28 days ago🌎 Remote📍 \⌛ Posted 28d ago
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
Location: Reddit has a flexible first workforce. Don’t live near our office? No worries: you can work remotely from anywhere in the US or Canada.
About the Team
The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem.
Responsibilities
- Design and build systems that improve the efficiency of ML training and inference workloads.
- Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
- Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.
- Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
- Build benchmarking frameworks and performance dashboards for training and serving systems.
- Optimize distributed training infrastructure, data pipelines, and model serving architectures.
- Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.
- Drive technical strategy for ML platform scalability, reliability, and cost efficiency.
Qualifications
Required
- BS, MS, or PhD in Computer Science or a related field.
- 5+ years of software engineering experience.
- Strong proficiency in Python
- Profiency in at least one systems language (Go, C++, Rust, or Java) preferred
- Experience building distributed systems at scale.
- Experience with machine learning infrastructure, training systems, or model serving platforms.
- Deep understanding of performance engineering and systems optimization.
- Strong debugging and profiling skills.
Preferred
- Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.
- Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark
- Familiarity with GPU architectures and performance analysis tools.
- Experience optimizing cloud infrastructure costs across large ML workloads.
- Contributions to internal platforms used by multiple ML teams.
- Experience with building real time ML inference applications
What Success Looks Like
- ML engineers can move from idea to experiment faster.
- Training and inference costs decrease, performance increases, while model quality is maintained or improved.
- GPU utilization and cluster efficiency increase.
- Platform reliability improves as ML workloads scale.
- Teams spend less time managing infrastructure and more time building models.
- Average recommendation model size increases.
Benefits:
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Group Personal Pension Scheme with Employer match
- Private Medical and Dental Scheme
- Income Replacement Programs
- Bike to Work scheme
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$230,000—$322,000 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
- BView description📍 Wahiawa, Hawaii⌛ Posted 28 days ago📍 Wahiawa, Hawaii⌛ Posted 28d ago
Job Description
Remote Work: No Job Number: R0249709 Location: Wahiawa,HI,US Artificial Intelligence and Machine Learning Engineer, SeniorThe Opportunity:
Cyber and intelligence analysts rely on multi‑step workflows that are time‑sensitive, detail‑rich, and critical to national security. As an Artificial Intelligence and Machine Learning Engineer, you will work directly with mission users to capture these workflows, document operational decision points, and translate them into effective AI‑enabled capabilities.
You will design and implement solutions that may include LLM‑powered workflows, agent‑based automation, or hybrid approaches depending on mission needs. Your work will streamline analytical tasks, improve data accessibility, and support rapid, informed decision‑making in high‑tempo environments.
You’ll collaborate with operators, analysts, developers, and mission leadership to ensure solutions integrate cleanly with existing systems, perform reliably in production, and adhere to the security and governance expectations of classified environments.
Join us. The world can’t wait.
You Have:
Experience capturing user workflows and translating them into structured process maps, automation requirements, or executable logic
Experience designing or implementing LLM‑based or agentic workflows, including multi‑step reasoning, tool integrations, and orchestration
Experience integrating AI systems with APIs, enterprise data stores, or mission platforms
Experience with programming languages such as Python
TS/SCI clearance with a polygraph
Bachelor’s degree and 3+ years of experience in AI and ML engineering, data science, or software engineering within cyber, intelligence, or national security environments, or 6+ years of experience in AI and ML engineering, data science, or software engineering within cyber, intelligence, or national security environments in lieu of a degree
Nice If You Have:
Experience engineering AI capabilities in on‑premise or multi‑classification environments
Experience with AWS or Azure, including work in restricted or classified environments
Experience with AI or LLM development frameworks such as LangChain, LangGraph, PydanticAI, or CrewAI
Experience with ML frameworks such as PyTorch, TensorFlow, vLLM, or llama.cpp
Experience with cyber or intelligence workflows, operational data types, or mission‑oriented analytical processes
Master’s degree in AI, ML, Data Science, Cybersecurity, or Engineering
Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with polygraph is required.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
About Us
Booz Allen is an advanced technology company. We build commercial-grade products and solutions for America’s most critical defense, civil, and national security priorities.
Applicants who need a reasonable accommodation for any part of the application, hiring, or employment process because of a disability, a sincerely held religious belief, practice, or observance, or as otherwise required by applicable law should contact the Booz Allen Help Desk by calling 1-877-927-8278 or sending an email to [email protected]. We will review requests on an individualized basis and provide reasonable accommodations consistent with applicable law.
- BView description📍 New York, New York⌛ Posted 28 days ago📍 New York, New York⌛ Posted 28d agoSenior Machine Learning Engineer - Artificial Intelligence
Description & Requirements
Bloomberg’s Engineering AI department has 450+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.
At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
Join the AI Group as a Senior ML Engineer and you will have the opportunity to:- Collaborate with colleagues on production systems and write, test, and maintain production quality code
- Design, train, experiment, and evaluate ML models, algorithms and solutions
- Demonstrate technical leadership by owning cross-team projects
- Stay current with the latest research in ML and incorporate new findings into our models and methodologies
- Represent Bloomberg at scientific and industry conference and in open-source communities
- Publish product and research findings in documentation, whitepapers or publications to leading academic venues
- Practical experience with solving Machine Learning problems and techniques
- Ph.D. in ML, Statistics or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields and 2+ years of relevant work experience
- Experience with machine learning and deep learning frameworks
- An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving
- Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders
- A track record of authoring publications in top conferences and journals is a strong plus
We give back to the technology community and you can read more about our outreach at: http://www.techatbloomberg.com/ai
Salary Range = 165,000 - 260,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success. Location New York Business Area Engineering and CTO Ref # 10053558 - HuddleMate - Answer every question in your next interview or meeting
- IView description📍 Sunnyvale, California⌛ Posted 28 days ago📍 Sunnyvale, California⌛ Posted 28d ago
About the Team
Agentic Foundations, part of New Verticals ML, builds the core AI/ML intelligence that powers high-quality, scalable agents at DoorDash, and proves it through flagship agent experiences such as the Ask grocery assistant. We operate as a closed loop: new models, evals, and representations make our agents better, and real-world agent usage surfaces the gaps that drive our next foundations work.
About the Role
We’re looking for a Senior Machine Learning Engineer to join Agentic Foundations with a primary focus on Vertical Agent Development. You will own the continuous improvement of our flagship agents, starting with the Ask Assistant, using an eval-driven loop to make them faster, more cost-efficient, and more reliable for millions of customers. You will also help us bring this approach to new agentic experiences for Merchants and Dashers, turning promising ideas into production-ready agents.
This is a chance to work at the intersection of LLMs, agents, post-training, and evals on problems that ship. You will partner closely with engineers working on agentic memory, agent-compatible product representations, and post-training of small language models (SLMs), so that what we learn from production agents feeds directly back into our foundations, and what we build there makes our agents better.
You will report into the engineering lead on our New Verticals AI/ML team. We expect this role to be hybrid with some time in-office and some time remote.
You’re excited about this opportunity because you will…
- Raise the quality of our Consumer agents: build and refine our eval harness-optimization loop to pinpoint failure modes, then iterate on prompts, tools, skills, and context, and measure the impact on real customer tasks.
- Find the best balance of quality, latency, and cost: run rigorous experiments, including fine-tuning open-weights models and deploying small language models (SLMs) where they can replace or augment larger LLMs.
- Launch new agents: take agentic opportunities for Merchants and Dashers from early exploration to production.
- Turn foundations into product impact: work with teammates on agentic memory, agent-compatible product representations, and post-training SLMs for steerable generative recommendation, and bring those capabilities into production agents.
- Shape the roadmap: partner with engineering, product, and business leaders to define an ML-driven strategy for our fast-growing grocery and retail delivery business.
We’re excited about you because you have…
- 3+ years of industry ML experience, including hands-on work building and shipping LLM-based agents (tool use, context management, prompting, guardrails) and improving them with evals and data
- Experience with post-training or fine-tuning of open-weights models (e.g., SFT, preference optimization, or RL), ideally including small language models, and sound judgment on quality, latency, and cost trade-offs
- Strong foundation in NLP and machine learning, with proficiency in Python and frameworks such as PyTorch or TensorFlow
- M.S. or PhD in Computer Science, Statistics, Math, or another quantitative field, or equivalent practical experience, plus a collaborative, growth-minded approach and a drive for measurable impact
Compensation
The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.
In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.
DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.
To learn more about our benefits, visit our careers page here.
See below for paid time off details:
- For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
- For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).
The national base pay ranges for this position within the United States, including Illinois and Colorado.
I4$137,100—$201,600 USDI5$167,800—$246,800 USDI6$203,500—$299,300 USDAbout DoorDash
At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods.
DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.
Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.
If you need any accommodations, please inform your recruiting contact upon initial connection.
Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only
We used Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provided Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023. We resumed using Covey Scout for Inbound again on June 29, 2024, and ceased using Covey Scout for Inbound on April 30, 2026.
The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: https://getcovey.com/nyc-local-law-144.
Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash . - BView description📍 Marine Corps Base Camp…⌛ Posted 28 days ago📍 Marine Corps Base Camp Lejeune, North Carolina⌛ Posted 28d ago
Job Description
Remote Work: No Job Number: R0250591 Location: Camp Lejeune,NC,US Artificial Intelligence and Machine Learning EngineerThe Opportunity:
Are you excited at the prospect of unlocking the secrets held by a data set? Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances?
As an MLOps Engineer, you have a passion for leveraging Department of War (DoW) data to drive operational readiness and tactical decision making. You excel at designing, building, and operationalizing scalable solutions in secure enterprise environments integrating datasets from disparate systems. As a member on our team, you’ll work directly with the client and stakeholders to architect data-driven solutions that enhance situational awareness and optimize mission execution. You will apply your deep technical knowledge in data orchestration and the development and deployment of solutions to production environments to inform the client’s technical strategy for designing and implementing complex systems.
Join us. The world can't wait.
You Have:
- Experience leading the deployment and operationalization of scalable AI microservices, including the development of production-grade APIs using containerization and orchestration, to deliver automated model serving and CI/CD pipelines for production application
- Experience with data orchestration and containerization tools, such as Docker, Kubernetes, NIFI, or Airflow, to design, deploy and maintain scalable ETL/ELT pipelines, data flows, and production microservices to cloud environments
- Experience leading or participating in cross-functional efforts to complete ATO accreditation for release of products in production environment
- Experience implementing MLOps best practices, including model monitoring, drift detection, and automated retraining workflows, while maintaining strict compliance in regulated cloud environments
- Experience with programming and scripting languages, such as Python, Java, Bash, Shell, SQL, HCL, YAML, JavaScript, or Typescript to support full-stack development efforts
- Experience communicating complex technical concepts to both technical and non-technical audiences
- Experience creating clear and comprehensive architecture diagrams, data flow diagrams, and system design documentation to support cross-functional collaboration and stakeholder alignment
- Knowledge of NIST SP 800-53 controls
- Secret clearance
- Bachelor's degree
Nice If You Have:
- Experience building ETL/ELT pipelines from external data lakes and systems such as the War Data Platform (WDP), Palantir Maven Smart System (MSS), Cloud Platforms such as Azure, AWS, or GCP, and SharePoint
- Experience with other DoW enterprise data platforms such as Advana or MSS
- Experience with Lean-Agile methodologies and frameworks such as Scrum or Scaled Agile Framework (SAFe)
- Experience managing project workflows and documentation across Jira and Confluence for alignment to concurrent initiatives
- Knowledge of USMC operational planning, intelligence cycles, or logistics processes
- TS/SCI clearance
- Master's degree in an Artificial Intelligence or Machine Learning field
Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Secret clearance is required.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.- Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
- Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen or customer facility, in alignment with your leadership's expectations and the needs of the role.
- Onsite: If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
About Us
Booz Allen is an advanced technology company. We build commercial-grade products and solutions for America’s most critical defense, civil, and national security priorities.
Applicants who need a reasonable accommodation for any part of the application, hiring, or employment process because of a disability, a sincerely held religious belief, practice, or observance, or as otherwise required by applicable law should contact the Booz Allen Help Desk by calling 1-877-927-8278 or sending an email to [email protected]. We will review requests on an individualized basis and provide reasonable accommodations consistent with applicable law.
- TView description🌎 Remote📍 ⌛ Posted 29 days ago🌎 Remote📍 \⌛ Posted 29d ago
At Thorn, our cause is our code. We are a nonprofit whose mission of defending children from sexual exploitation and abuse is deeply embedded within our core—a shared code that drives us to do challenging work with resilience and determination.
Here, you’ll work and grow among the best hearts and the best minds in tech, data, and business alongside our network of independent partners, NGOs, and law enforcement agencies. Together, we’re focused on building technology that protects children’s futures. We are looking for dynamic problem solvers with the desire to help address some of today’s toughest issues. You’ll collaborate with a diverse group of peers in a remote environment centered on wellness, care, and compassion.
In 2019, we took the stage atTED and shared our audacious goal of eliminating child sexual abuse material from the internet. Come join us to help make this goal a reality and build a world where every child can be safe, curious, and happy.
About the Role
As Thorn’s Director of Machine Learning & AI, you will lead and build the team responsible for applying machine learning and AI to some of the most difficult technical challenges in our mission. You will shape and lead the strategy for the function, develop its people and technical leaders, and ensure ML expertise is deeply integrated into Thorn’s products, technical innovation, and broader Build strategy.
You will lead an established core of passionate ML engineers with deep technical and mission expertise, while also having the opportunity to grow the team and shape the capabilities Thorn will need next. This role requires an exceptional people leader who can earn trust, build on the strengths already present, recruit outstanding new talent, and help the team evolve as Thorn’s needs and technical opportunities change.
As a member of Build leadership, you will report to the CTO and partner closely with Engineering, Product, and other teams across the organization to align ML priorities and technical direction with Thorn’s broader strategy.
What You’ll Do
Technical Strategy and Innovation
- Shape and lead Thorn’s Machine Learning and AI strategy in partnership with Build leadership, Product, and cross-functional stakeholders, evolving technical direction as emerging technologies, research, customer needs, and the child safety landscape change.
- Identify promising ML and AI technologies and approaches, translating research and experimentation into recommendations about where Thorn should invest, partner, build, or evolve its product and technology strategies.
- Support Thorn’s Technical Innovation Roadmap through the exploration, prototyping, de-risking, and validation of new technical capabilities to advance mission impact and inform future product strategy.
- Ensure ML systems and practices meet Thorn’s expectations for privacy, security, responsible AI, regulatory compliance, reliability, and operational excellence, including appropriate oversight of sensitive datasets, external data annotation partners, and CSAM reporting processes.
- Partner closely with the Business Development and Strategic Impact (BDSI) team to inform Thorn’s technical research roadmap and enable exploration by connecting research questions, ML expertise, emerging opportunities, and product needs.
Develop an Exceptional ML Team
- Build on the strengths of an established, highly skilled Machine Learning team while developing the people, leadership, and capabilities Thorn will need next.
- Recruit, develop, empower, and retain exceptional ML talent, maintaining a high bar for technical excellence, collaboration, curiosity, and mission alignment.
- Lead, coach, and develop technical leaders and individual contributors of various levels, creating clear ownership and meaningful opportunities for people to grow their skills and their impact.
- Earn trust through curiosity, consistency, transparency, active listening, and strong follow-through.
- Thoughtfully evolve team culture and ways of working as Thorn’s needs change, preserving the strengths already present while strengthening collaboration, adaptability, and shared ownership.
- Foster psychological safety alongside high expectations, healthy disagreement, technical excellence, continuous learning, and accountability.
- Set clear expectations and provide timely, candid feedback. Recognize strong performance and address performance concerns thoughtfully and directly.
- Build leadership capacity throughout the team, delegating ownership and decision-making to the appropriate leaders and experts.
- Partner with People & Culture on hiring, onboarding, development, performance management, and succession planning, in ways that strengthen team cohesion, uphold our values, and support a culture of excellence and care.
One Build Collaboration
- Build deep partnerships across Machine Learning, Engineering, Product, BDSI, and other teams, strengthening collaboration across the SDLC so research, experimentation, product development, and production delivery remain connected throughout the lifecycle.
- Partner closely with Engineering leadership and teams to ensure ML capabilities are designed, built, deployed, and operated as reliable, scalable, production-ready systems, with shared technical context and clear ownership.
- Partner with Build leadership and Technical Program Management to align ML priorities, dependencies, investments, and capacity with Build’s broader strategy and roadmap.
- Help shape cross-Build technical decisions by bringing ML expertise and perspective, while strengthening collaboration across disciplines and empowering the appropriate teams and technical leaders to own decisions within their areas.
- Partner with Product, Engineering, BDSI, and customer-facing teams to ensure customer and ecosystem learning informs ML priorities and continuous improvement.
- Partner across Build to strengthen shared approaches to responsible data use, privacy, security, and ML governance.
Execution and Organizational Leadership
- Establish clear priorities, expectations, and operating rhythms that help the ML team deliver predictably while maintaining space for innovation and learning.
- Ensure sustainable ML development and operational practices that appropriately balance speed, quality, reliability, cost, security, and long-term maintainability.
- Empower technical leaders and senior individual contributors to own day-to-day execution while maintaining visibility into progress, risks, dependencies, and organizational needs.
- Partner with Finance and Build leadership on responsible resource allocation, headcount planning, infrastructure investment, and budget stewardship.
- Identify organizational or technical constraints early, make clear tradeoffs, and help teams align and move forward when priorities or perspectives compete.
- Serve as a member of Build’s leadership team, contributing to Build strategy, organizational planning, emerging threat response, investment decisions, and complex problem-solving.
- Represent Thorn’s ML work externally with customers, strategic partners, funders, conferences, advisory groups, and the broader technical community as appropriate.
What We’re Looking For
Technical Strategy and Execution
- Significant experience leading ML, AI, Data Science, or related technical teams responsible for production capabilities at meaningful scale.
- Strong technical judgment across modern ML and AI, with the ability to guide direction, evaluate tradeoffs, and translate emerging technologies and research into practical capabilities and strategic direction.
- Deep understanding of AI/ML applications, content detection technologies, and software development.
- Experience developing and operating ML capabilities with appropriate attention to reliability, evaluation, monitoring, privacy, security, and responsible AI.
Team Culture and Cross-functional Collaboration
- Proven ability to lead, develop, and strengthen high-performing technical teams, including attracting, hiring, and retaining exceptional talent.
- Experience coaching technical leaders and individual contributors, delegating ownership appropriately, setting clear expectations, and providing candid, constructive feedback.
- Ability to earn trust with an established team and thoughtfully evolve culture while fostering psychological safety, accountability, inclusion, and high expectations.
- Track record of strong collaboration with Engineering, Product, Research/BDSI, and other cross-functional partners, including moving capabilities from research and experimentation into reliable production systems.
- Skilled at navigating complex stakeholder environments, creating alignment across teams, and providing direction and coaching where needed.
Leadership
- Ability to influence, drive change, and solve complex problems calmly and strategically.
- Strong communication skills, including asking critical questions, communicating key points clearly, and representing technical work externally through partner conversations, conferences, fundraising events, or advisory forums.
- Lead with empathy, humility, honesty, clarity, and a trauma-informed approach.
- Build relationships based on trust, transparency, accountability, and follow-through.
- You have a commitment to putting the children we serve at the center of everything you do.
Compensation and Benefits
A reasonable estimate of the compensation range for this role is $188,000 - $302,450/year. This range takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to location; skill sets; experience and training; licensure, and certifications.
Our remote-first work model is structured around working from home most of the time. But, there will be times that employees are expected to travel. For example, Thorn may host company-wide gatherings, and smaller teams may hold in-person meetings and team-building events, or require attendance at specific conferences.
At Thorn, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Thorn can mean for you.
Thorn is strengthened by the wide range of experiences and perspectives on our team. We value the diversity of our professional backgrounds, subject matter expertise, cultures, and perspectives because they help us solve complex problems and serve our mission more effectively. We hire based on merit, qualifications, and organizational need, and we are committed to fostering an inclusive environment where all employees can thrive.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Thorn is committed to the full inclusion of all qualified individuals. We provide reasonable accommodations to ensure candidates and employees with disabilities can fully participate in the application process, perform essential job functions, and access all the benefits and privileges of employment. If you need an accommodation, please contact us at [email protected]
Know Your Rights: Workplace discrimination is illegal
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- RView description🌎 Remote📍 ⌛ Posted 29 days ago🌎 Remote📍 \⌛ Posted 29d ago
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform.
This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness.
You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact.
This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging.
What you’ll do:
- Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field.
- Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance.
- Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization.
- Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale learning and serving: storage/retrieval for embeddings, feature pipelines, and APIs. Collaborate with ML/Ranking infra to ensure low-latency serving, high availability, and integration with MLOps systems.
- Drive Cross-Team Integration & Impact: Partner with Feeds, Notification, Search and Ads teams to drive experimentation and adoption of new user understanding models with product teams across Reddit, ensuring measurable end-to-end impact on key metrics.
- Set Technical Bar & Mentor: Mentor senior to staff engineers, lead design reviews, steward technical decisions across the user understanding domain, and champion and drive engineering processes and best practices
Who you might be:
- You have at least 10 years experience building and scaling production-grade ML systems, particularly in user modeling, large-scale representation learning, or recommender systems.
- You have a track record of driving ambiguous, high-impact initiatives from concept to production, shaping both technical direction and execution.
- You are product- and impact-oriented: you care deeply about how your work moves real metrics (e.g., engagement, retention, revenue), not just model quality.
- You bring strong fundamentals in mainstream user understanding ML approaches (e.g., representation learning, behavioral modeling, user clustering), and understand their trade-offs in real-world systems.
- You are excited about the GenAI shift and have experience (or strong intuition) applying LLMs or foundation models to evolve existing systems, going beyond incremental improvements.
- You think in systems, not just models: you consider data, training, evaluation, serving, and adoption as a cohesive whole, and design with end-to-end impact in mind.
- You influence beyond your immediate team: partnering effectively with product, infra, and other ML teams, and driving alignment across multiple stakeholders.
- You raise the technical bar: mentoring senior engineers, leading design reviews, and establishing best practices for building reliable, scalable ML systems.
- You are comfortable navigating trade-offs across quality, latency, cost, and safety, especially in large-scale, user-facing systems.
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-remote, #LI-JS5
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$266,000—$372,400 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
- FView description - by The SaaS Jobs Board📍 Bengaluru, Karnataka,…⌛ Posted 30 days ago📍 Bengaluru, Karnataka, India⌛ Posted 30d ago
Company Description
Organizations everywhere struggle under the crushing costs and complexities of “solutions” that promise to simplify their lives. To create a better experience for their customers and employees. To help them grow. Software is a choice that can make or break a business. Create better or worse experiences. Propel or throttle growth. Business software has become a blocker instead of ways to get work done.
There’s another option. Freshworks. With a fresh vision for how the world works.
At Freshworks, we build uncomplicated service software that delivers exceptional customer and employee experiences. Our enterprise-grade solutions are powerful, yet easy to use, and quick to deliver results. Our people-first approach to AI eliminates friction, making employees more effective and organizations more productive. Over 72,000 companies, including Bridgestone, New Balance, Nucor, S&P Global, and Sony Music, trust Freshworks’ customer experience (CX) and employee experience (EX) software to fuel customer loyalty and service efficiency. And, over 4,500 Freshworks employees make this possible, all around the world.
Fresh vision. Real impact. Come build it with us.
Job Description
The Impact You Will Create
As a Staff Machine Learning Engineer, you will serve as the critical architectural bridge between cutting-edge Data Science research and massive-scale, product-ready implementation. You will move beyond standard feature delivery to define the technical vision and infrastructure that brings sophisticated algorithms to life. Your work will directly result in:
- Massive Scale & Reliability: Architecting and deploying robust ML APIs and pipelines capable of serving millions of requests with ultra-low latency and unwavering reliability.
- Engineering Excellence: Setting the gold standard for ML Engineering practices, MLOps, and system design across the organization.
- Accelerated AI Innovation: Transforming theoretical models into high-performance, production-grade systems, directly shrinking the time-to-market for complex ML business solutions.
- Cross-Organizational Multiplier: Acting as a strategic technical anchor, influencing cross-product architects, leading POCs, and mentoring teams to ensure tight technical alignment across all engineering groups.
Roles & Responsibilities
- End-to-End Pipeline Architecture: Architect, build, and manage comprehensive, highly scalable ML pipelines covering data pre-processing, model generation, automated deployment, cross-validation, and active feedback loops.
- ML Algorithm Implementation: Partner deeply with Data Scientists to translate complex, theoretical ML models and algorithms into high-performance, production-grade code.
- High-Performance Service Delivery: Design, develop, and deploy highly extensible ML API services rigorously optimized for low latency and massive scalability.
- Operational Intelligence & Observability: Devise and build advanced monitoring capabilities to track both engineering system health and ML model performance metrics (drift, accuracy, etc.) over the long term.
- Strategic Innovation & Architecture: Architect solutions from scratch, leading Proof of Concept (POC) initiatives across various tech stacks to validate optimal solutions for complex business challenges.
- Technical Leadership & Execution: Own the full lifecycle of feature delivery autonomously—from requirement gathering with product stakeholders to final deployment—while collaborating with cross-product architects to drive platform adoption.
Qualifications
- Experience: 9+ years of progressive, highly relevant experience in software engineering and machine learning development.
- Production Excellence: A proven, demonstrable track record of successfully architecting, building, and productionizing complex Machine Learning solutions at an enterprise scale.
- MLOps Mastery: Deep, practical experience with modern MLOps practices, ensuring seamless, automated, and secure model transitions from development and training into production environments.
- Education: A Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field.
Skills
- Core Programming: Expert-level Object-Oriented Programming (OOP) expertise in Python and Java.
- ML & Deep Learning Frameworks: Mastery of industry-standard ML libraries and Deep Learning frameworks, including PyTorch, Keras, TensorFlow, and TFServing.
- Foundational Engineering: Deep, advanced understanding of Data Structures, Algorithms (DSA), and complex, distributed System Design.
- Cloud & Infrastructure: Hands-on knowledge and proficiency with Cloud infrastructure and services (AWS highly preferred) for large-scale data processing and ML model hosting.
- Analytical Problem Solving: Exceptional analytical and debugging skills with a relentless focus on algorithmic optimization, resource efficiency, and resolving bottlenecks in distributed systems.
Additional Information
Please note this is a hybrid role from Bengaluru that requires an in-office presence 3 days / week (Tue-Thu).
At Freshworks, we have fostered an environment that enables everyone to find their true potential, purpose, and passion, welcoming colleagues of all backgrounds, genders, sexual orientations, religions, and ethnicities. We are committed to providing equal opportunity and believe that diversity in the workplace creates a more vibrant, richer environment that boosts the goals of our employees, communities, and business. Fresh vision. Real impact. Come build it with us.
- FView description - by EchoJobs🌎 Remote📍 San Jose, CA, US⌛ Posted 8 days ago🌎 Remote📍 San Jose, CA, US⌛ Posted 8d ago
Senior Principal Engineer at F5 with a salary of $259K - $389K.
- JobCopilot - Get 10x more Job Interviews
- RView description - by EchoJobs🌎 Remote⌛ Posted 8 days ago🌎 Remote⌛ Posted 8d ago
AI Developer (Remote) at Robusta Technology Group Worldwide.
- AView description - by 4 Day Week📍 United States⌛ Posted 9 days ago📍 United States⌛ Posted 9d ago
Worker Type
Supplemental
Job Description
Intern – Machine Learning (Computer Vision)
Summary
Summer Internship Program
Our paid Summer Internship Program is designed to provide students with an immersive, hands-on experience within the aerospace and defense industry. Interns work alongside AV team members on meaningful projects involving cutting-edge technology while developing professional relationships, strategic problem-solving skills, and practical experience in a full-time work environment.
This is a 12-week, onsite program intended for highly motivated and passionate students who are currently enrolled in college or are recent graduates. Applicants must have a minimum 3.0 GPA, with a preference for students at the junior level or above.
Our program has been recognized by Yello and WayUp as one of the Top 100 Internship Programs in the United States for multiple years.
Depending on the team and location, students who are willing to relocate for their internship may be eligible for a relocation and housing reimbursement stipend.
AV offers internship opportunities across various teams and locations throughout the United States. Specific team, location, and program details will be discussed during the interview process.
As a Machine Learning Intern, you will have the opportunity to support the R&D Group at AV in developing innovative computer vision solutions for defense and commercial applications. You will contribute to small, focused design teams working on detection, classification, localization, and tracking technologies. This internship will expose you to various stages of the development process including concept design, prototyping, testing, and evaluation.
Position Responsibilities- Support the development of computer vision and machine learning algorithms for detecting, classifying, localizing, and tracking objects-of-interest using UAV-mounted gimballed cameras.
- Assist in writing and testing software to integrate ML algorithms into aircraft systems (e.g., autopilots, payloads, robotic platforms).
- Explore and visualize data to understand distribution patterns and potential anomalies.
- Assist in implementing machine learning systems and validating designs through experiments.
- Help define objectives, develop models, and track their performance using metrics.
- Perform data analysis tasks using AV tools and industry-standard platforms.
- Help manage project resources such as datasets, hardware, and time to support project timelines.
- Contribute to the evaluation of ML algorithm performance and model deployment strategies.
- Participate in data preparation activities, including cleaning and transformation.
- Assist in error analysis and developing corrective strategies.
- Research and experiment with appropriate ML algorithms and tools.
- Support running tests and experiments on selected datasets and data representations.
- Follow standard procedures to analyze data and support development tasks.
- Perform other duties as assigned.
Basic Qualifications (Required Skills & Experience)
- Currently pursuing a BS in Computer Vision, Machine Learning, Computer Science, Electrical Engineering, or a related field.
- Familiarity with C/C++ and MATLAB.
- Proficiency with office productivity tools.
- Basic troubleshooting skills for technical systems.
Other Skills & Qualifications
- Exposure to deep learning frameworks (e.g., TensorFlow, Keras).
- Familiarity with Python and libraries such as scikit-learn and pandas.
- Experience with data visualization and handling large datasets.
- Exposure to OpenCV and working in a Linux environment.
- Understanding of key concepts in:
- Machine learning
- Computer vision
- Mathematical optimization
- Data mining
- Predictive analytics
- Ability to assist in selecting hardware/software for model deployment.
Preferred Qualifications
- Effective communication and teamwork skills.
- Strong initiative and eagerness to learn in a fast-paced R&D environment.
- Willingness to take ownership of tasks and learn from feedback.
- Ability to adapt to changing priorities and work independently under supervision.
Physical Demands
- Ability to work in an office and lab environment.
- May be required to sit or stand for long periods, use hands/fingers for computer and communication tasks.
Clearance Level
No Clearance
The salary range for this role is:
AeroVironment considers several factors when extending an offer, including but not limited to, the location, the role and associated responsibilities, a candidate’s work experience, education/training, and key skills.
ITAR Requirement:
This position requires access to information that is subject to compliance with the International Traffic Arms Regulations (“ITAR”) and/or the Export Administration Regulations (“EAR”). In order to comply with the requirements of the ITAR and/or the EAR, applicants must qualify as a U.S. person under the ITAR and the EAR, or a person to be approved for an export license by the governing agency whose technology comes under its jurisdiction. Please understand that any job offer that requires approval of an export license will be conditional on AeroVironment’s determination that it will be able to obtain an export license in a time frame consistent with AeroVironment’s business requirements. A “U.S. person” according to the ITAR definition is a U.S. citizen, U.S. lawful permanent resident (green card holder), or protected individual such as a refugee or asylee. See 22 CFR § 120.15. Some positions will require current U.S. Citizenship due to contract requirements.
Benefits: AV offers an excellent benefits package including medical, dental vision, 401K with company matching, a 9/80 work schedule and a paid holiday shutdown. For more information about our company benefit offerings please visit: http://www.avinc.com/myavbenefits.
We also encourage you to review our company website at http://www.avinc.com to learn more about us.
Principals only need apply. NO agencies please.
About AV:
AV isn’t for everyone. We hire the curious, the relentless, the mission-obsessed. The best of the best.
We don’t just build defense technology—we redefine what’s possible. As the premier autonomous systems company in the U.S., AV delivers breakthrough capabilities across air, land, sea, space, and cyber. From AI-powered drones and loitering munitions to integrated autonomy and space resilience, our technologies shape the future of warfare and protect those who serve.
Founded by legendary innovator Dr. Paul MacCready, AV has spent over 50 years pushing the boundaries of what unmanned systems can do. Our heritage includes seven platforms in the Smithsonian—but we’re not building history, we’re building what’s next.
If you're ready to build technology that matters—with speed, scale, and purpose—there’s no better place to do it than AV.
We are proud to be an EEO/AA Equal Opportunity Employer, including disability/veterans. AeroVironment, Inc. is an Equal Employment Opportunity (EEO) employer and welcomes all qualified applicants. Qualified applicants will receive fair and impartial consideration without regard to race, sex, color, religion, national origin, age, disability, protected veteran status, genetic data, sexual orientation, gender identity or other legally protected status.
ITAR
U.S. Citizenship required. Must be willing to work on government contracts and have the ability to obtain a security clearance. - UView description🌎 Remote📍 USA-Remote(WA), District…⌛ Posted 23 days ago🌎 Remote📍 USA-Remote(WA), District Of Columbia⌛ Posted 23d ago
The Role
We are seeking a Senior ML engineer to design and evolve Unity Vector’s online model inference platform. This role focuses on building reliable infrastructure for serving machine learning models in production, optimizing inference performance, and enabling safe, efficient experimentation across high-traffic online systems.
You will work closely with ML engineers, platform teams, and product stakeholders to ensure models can be deployed, scaled, monitored, and iterated on efficiently. You will play a key role in shaping how models are packaged, served, validated, monitored, and optimized in production environments.This role requires strong systems thinking, deep experience with production ML infrastructure, and the ability to drive architectural improvements across teams.
What you'll be doing
- Design and operate large-scale online inference infrastructure that serves production ML models with low latency and high reliability, such as PyTorch, Triton Inference Server, Kubernetes, GKE, Ray, or similar distributed serving frameworks.
- Develop infrastructure that supports distributed training workflows using technologies such as Pytorch, Ray Data, and Ray Train, etc.
- Integrate ML pipelines with workflow orchestration systems (e.g., Flyte, Airflow, or similar) to enable reliable multi-stage training workflows
- Optimize model performance through model compilation, GPU/CPU utilization improvements, request scheduling, kernel fusion, and runtime-level tuning.
- Improve observability of ML systems through latency, throughput, error-rate, cost, saturation, and model-health monitoring.
- Partner closely with ML engineers to support faster model iteration while maintaining production safety, scalability, and cost efficiency.
- Improve the reliability and reproducibility of model serving workflows, including model packaging, artifact validation, compatibility testing, and deployment automation.
- Lead architectural improvements that make the online ML platform more robust, user-friendly, scalable, and cost-efficient.
What we're looking for
- Experience building and operating production-grade online ML inference systems, such as NVIDIA Triton Inference Server, TorchServe, Ray Serve, TensorFlow Serving, or similar systems.
- Experience with model serving frameworks such as NVIDIA Triton Inference Server, TorchServe, Ray Serve, TensorFlow Serving, or similar systems.
- Experience optimizing inference workloads using techniques such as dynamic batching, model compilation, quantization, GPU acceleration, GPU kernel optimization, caching, or runtime tuning.
- Strong experience with distributed systems, Kubernetes, autoscaling, service reliability, and production observability.
- Strong programming skills in Python, with practical experience working on production ML systems and high-scale services.
- Experience with PyTorch and modern model deployment workflows, including model packaging, validation, and serving lifecycle management.
- Experience designing infrastructure for safe model rollout, canary testing, A/B experimentation, and automated rollback.
- Strong systems thinking, with the ability to reason about latency, throughput, reliability, scalability, and cost tradeoffs in online systems.
- Proven ability to lead technical direction and influence architectural decisions across teams without formal authority.
Additional information
Zone A: $210,300 - $273,400
Zone B: $187,200 - $243,300
Zone C: $165,600 - $215,200
This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set.
Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.
Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.
While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program
Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.
Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
This posting is intended to fill an existing vacancy, and we are committed to providing applicants with updates throughout the hiring process in accordance with applicable law.Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.
Your privacy is important to us. Please take a moment to review our Prospect and Applicant Privacy Policies. Should you have any concerns about your privacy, please contact us at [email protected]. - HuddleMate - Answer every question in your next interview or meeting
- AView description📍 New York, NY⌛ Posted 24 days ago📍 New York, NY⌛ Posted 24d ago
At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.
In this role you will Build robust batch/streaming data pipelines and transformations that ensure high‑quality, governed data flows into AI and analytics platforms. Implement data modeling, quality checks, lineage/metadata, performance optimization, and reliable orchestration across cloud and Lakehouse environments. The position is located in Jersey City, NJ.
In this role, you’ll make an impact in the following ways:
- Design, build, and optimize batch and streaming data pipelines that deliver high-quality, governed data to AI, analytics, and enterprise platforms.
- Develop scalable transformation frameworks across cloud and lakehouse environments with a strong focus on reliability, performance, and cost efficiency.
- Implement data modeling, schema design, lineage, metadata, and data quality controls to create trusted, reusable data assets.
- Build and support orchestration and workflow automation for complex pipelines and dependencies using modern data engineering tools.
- Partner with analytics, AI, business, and technology teams to translate requirements into scalable, secure, and governed data solutions.
- Resolve complex platform and pipeline issues related to performance, reliability, integration, and data quality.
- Promote engineering best practices in distributed processing, testing, monitoring, security, and continuous improvement.
- Provide technical leadership and mentoring while contributing to the adoption of modern data engineering and lakehouse capabilities.
To be successful in this role, we’re seeking the following:
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- 9–11 years of experience in software development and data engineering; financial services experience is a plus.
- Strong experience building large-scale batch and streaming data pipelines and backend data environments.
- Deep expertise in Spark/Databricks, Kafka, SQL, and orchestration tools such as Airflow and/or dbt.
- Strong understanding of cloud and lakehouse architectures, distributed processing, and storage formats such as Parquet and Delta.
- Experience with data modeling, schema design, lineage, metadata, and data quality frameworks.
- Proven ability to improve performance, scalability, reliability, cost efficiency, and governance across data platforms.
- Strong stakeholder management, problem-solving, and technical leadership skills, including mentoring engineers and leading complex delivery.
At BNY, our culture speaks for itself, check out the latest BNY news at:
BNY Newsroom
BNY LinkedIn
Here’s a few of our recent awards:
America’s Most Innovative Companies, Fortune, 2025
World’s Most Admired Companies, Fortune 2025
“Most Just Companies”, Just Capital and CNBC, 2025
Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $126,000 and $210,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs.
This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.
How to Find Machine Learning Jobs: Your Comprehensive Guide 🤖
Machine learning professionals are in high demand across industries such as E-commerce, Financial Services, Healthcare, Education, Media, SaaS, Travel, Real Estate, Cybersecurity, and Gaming. This guide will help you navigate the machine learning job market and maximize your chances of landing your ideal role.
Why Consider Machine Learning Jobs?
- High-impact applications in AI, automation, and data-driven decision making
- Opportunities for career growth in both startups and established companies
- Dynamic work environment with the chance to work on cutting-edge projects
How to Find Machine Learning Jobs
- Use Advanced Search Filters: Filter job listings by technology stack (Python, TensorFlow, PyTorch, Scikit-learn, Keras, etc.), location, and posting date. Set up alerts for new jobs matching your skills and interests.
- Check Company Career Pages: Visit the websites of companies you admire and monitor their career sections for the latest machine learning openings. Sign up for company newsletters for job updates.
- Leverage Social Media and Networking: Follow tech companies and industry leaders on social media. Join machine learning, AI, and data science communities and forums. Engage with posts and participate in discussions to increase your visibility.
Tips for Applying to Machine Learning Jobs
- Customize your resume and cover letter for each application
- Highlight relevant experience with ML frameworks, data science tools, and statistical modeling
- Showcase your portfolio, GitHub projects, or research publications
- Prepare for interviews by reviewing ML fundamentals, statistics, and practicing technical case studies
- Follow up after applying to show continued interest
Frequently Asked Questions (FAQs)
1. What are the most in-demand machine learning roles?
Machine Learning Engineer, Data Scientist, AI Research Scientist, Computer Vision Engineer, NLP Engineer, Deep Learning Engineer, MLOps Engineer, Data Engineer, Robotics Engineer, and Machine Learning Architect are highly sought after.
2. How can I improve my chances of getting hired in machine learning?
Build a strong portfolio, contribute to open-source projects, stay updated on ML trends, and network with other professionals in the field.
3. Are remote machine learning jobs available?
Yes, many companies offer remote or hybrid work options for machine learning professionals, especially for experienced candidates.
4. What should I include in my machine learning CV?
Include personal details, education, technical skills, work experience, portfolio or research links, and references. Highlight your experience with ML frameworks, data analysis, and successful projects.
5. How do I prepare for machine learning interviews?
Review ML fundamentals, practice coding and algorithm challenges, and be ready to discuss your previous projects and problem-solving approaches.
6. Is it important to follow up after applying?
Yes, a polite follow-up can demonstrate your enthusiasm and keep you top of mind with employers.
7. What are the typical working hours for machine learning professionals?
Standard working hours are usually 9:00 AM to 6:00 PM, but this can vary by company and project deadlines.
8. Are there opportunities for international candidates?
Yes, especially for skilled machine learning professionals. Ensure you meet visa and work permit requirements if applying abroad.
9. How can I stay updated on new machine learning job openings?
Set up job alerts, subscribe to company newsletters, and regularly check career pages.
10. What is the best way to network as a machine learning professional?
Attend AI/ML conferences, join machine learning and data science communities, and connect with professionals on social media platforms.
Conclusion
Finding a machine learning job requires a proactive approach, tailored applications, and effective networking. By following these strategies, you can enhance your job search and secure rewarding opportunities in this dynamic field.
Take a look at the list of job boards with Machine Learning Jobs or Data Science Jobs