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AI System Research and Development Engineer - Optimization

Develop and optimize GPU kernels and deep learning systems for LLM training and inference at Snowflake AI Research. Requires 5+ years in GPU/HPC optimization and strong proficiency in PyTorch, TensorFlow, JAX, and CUDA.

200k – 265kBellevue, WAML EngineeringOnsite5+ YOE

About the role

Responsibilities

  • Analyze and optimize GPU kernel performance for training and inference of LLMs
  • Develop and implement strategies to enhance the efficiency and scalability of deep learning systems
  • Profile and benchmark deep learning systems using tools and techniques to identify bottlenecks
  • Design and implement optimizations to reduce latency and improve resource utilization for training and inference
  • Stay updated with the latest advancements in GPU kernel optimization, deep learning, and LLM system development
  • Contribute to the development of agentic frameworks and applications for LLM-driven workflows, enhancing automation, reasoning, and decision-making capabilities
  • Open-source and publish innovations, optimizations, and engineering practices in technical blogs, top-tier conferences and journals

Requirements

  • Bachelor’s degree in Computer Science, Electrical Engineering, or a related field (Master’s degree or PhD preferred)
  • 5 years of experience in GPU kernel optimization, deep learning system optimization, or high-performance computing (HPC)
  • Proficiency in deep learning frameworks such as PyTorch, TensorFlow, JAX
  • Strong understanding of GPU architectures and experience with CUDA or similar frameworks
  • Experience with frameworks like CUTLASS, Triton, cuDNN, etc.
  • Experience with profiling tools (e.g., nvprof, Nsight) and performance analysis methodologies
  • Solid problem-solving skills and ability to debug complex performance issues
  • Excellent communication skills and ability to work effectively in a cross-functional team environment

Skills

PyTorchTensorFlowJAXCUDACutlassTritonCudnnNvprofNsightGpu Kernel Optimization

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