AI Engineer – New College Graduate

Job Description:

• Develop large-scale, highly available AI cloud services, including GPU virtual machines, bare-metal services, container services, cloud networking, storage, billing, monitoring, security, and multi-region resource management
• Develop managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
• Develop distributed training, model fine-tuning, model deployment, inference acceleration, serverless inference, model APIs, model evaluation, and production-grade LLM and multimodal model-serving capabilities
• Develop enterprise AI Agent platforms, including Agent building, workflow orchestration, tool integration, retrieval-augmented generation, memory systems, sandbox execution, multi-Agent collaboration, evaluation, observability, security, and large-scale Agent runtime infrastructure
• Develop GPU resource scheduling, distributed systems, high-performance networking, cloud-native infrastructure, MLOps and LLMOps platforms, AI application marketplaces, and automated operation systems for large-scale AI infrastructure
• Start in one of the listed technical areas based on interview assessment and business needs
• Rotate across different roles as part of career development

Requirements:

• Fresh graduates (Bachelors, Masters, PhD) from all disciplines and/or candidates with up to 2 years of related work experience
• Strong programming ability in one or more languages, including Go, Python, C++, Java, Rust, or related technologies
• Experience with Kubernetes, Docker, Helm, Terraform, OpenStack, Prometheus, Grafana, Argo, Istio, PostgreSQL, Redis, message queues, distributed storage, or other cloud-native technologies is highly preferred
• Experience developing or operating large-scale cloud platforms, Kubernetes platforms, AI training platforms, inference platforms, or Agent platforms is highly preferred
• Deep enthusiasm for cutting-edge AI infrastructure, cloud-native technologies, and building large-scale, globally distributed systems
• Proven achievements in academics, engineering projects, top-tier publications, open-source contributions, or programming/algorithm competitions
• Strong ownership mentality and engineering discipline
• Commitment to creating meaningful impact early in your career

Benefits:

• Opportunities to rotate across different roles as part of career development
• Culture that values authenticity and diverse perspectives
• Inclusive, respectful environment with open workspaces and an energetic, start-up spirit
• Opportunities to network with industry pioneers and enthusiasts
• Ability to contribute directly and make an impact on the future of the digital asset and AI computing industry
• Involvement in new projects and developing processes/systems
• Personal accountability, autonomy, rapid growth, and learning opportunities
• Training and mentoring
• Equal employment opportunities