Senior Deep Learning Software Engineer, Inference, Model Optimization

NVIDIA  ยท  via Remote Communications Jobs
๐Ÿ’ฐ $184,000 - $356,500/yr ๐ŸŒŽ Remote ๐Ÿ“ Remote, California

Job Description:

  • Train, develop, and deploy state-of-the-art generative AI models such as LLMs and diffusion models using NVIDIA's AI software stack
  • Leverage and build upon the Torch 2.0 ecosystem, including TorchDynamo, torch.export, and torch.compile, to analyze and extract standardized model graph representations from arbitrary Torch models
  • Develop high-performance inference optimization techniques, including automated model sharding, tensor parallelism, sequence parallelism, and efficient attention kernels with KV-caching
  • Collaborate with teams across NVIDIA to integrate performant kernel implementations into the automated deployment solution
  • Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities
  • Continuously innovate inference performance for NVIDIA's TRT, TRT-LLM, and TRT Model Optimizer software solutions
  • Architect and design a modular, scalable software platform supporting broad model coverage and optimization techniques

Requirements:

  • Masters, PhD, or equivalent experience in Computer Science, AI, Applied Math, or related field
  • 8+ years of relevant work or research experience in Deep Learning
  • Excellent software design skills, including debugging, performance analysis, and test design
  • Strong proficiency in Python, PyTorch, and related ML tools (e.g. HuggingFace)
  • Strong algorithms and programming fundamentals
  • Good written and verbal communication skills and the ability to work independently and collaboratively in a fast-paced environment
  • Contributions to PyTorch, JAX, or other Machine Learning Frameworks
  • Knowledge of GPU architecture and compilation stack, and capability of understanding and debugging end-to-end performance
  • Familiarity with NVIDIA's deep learning SDKs such as TensorRT
  • Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton

Benefits:

  • Highly competitive salaries
  • Comprehensive benefits package
  • Equity