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Snowflake DEEP LEARNING SYSTEM OPTIMIZATION ENGINEER 
United States, Washington, Bellevue 
239355199

02.08.2024
RESPONSIBILITIES:
  • Analyze and optimize GPU kernel performance for deep learning models.
  • 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.
  • Build a strong system foundation for Snowflake Arctic by interacting with model scientists for model-system co-development.
  • Stay updated with the latest advancements in GPU kernel optimization, deep learning, and LLM system development.
  • Publish their 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. A Master’s degree or PhD is preferred.
  • 5 years of experience in GPU kernel optimization, deep learning system optimization, or high-performance computing (HPC).
  • Proficiency in programming languages such as C/C++ and Python.
  • Strong understanding of GPU architectures and experience with CUDA or similar frameworks.
  • Experience with profiling tools (e.g., nvprof, Nsight) and performance analysis methodologies.
  • Solid problem-solving skills and ability to debug complex performance issues.
  • Experience with version control systems (e.g., Git) and collaborative development practices.
  • Excellent communication skills and ability to work effectively in a cross-functional team environment.

The following represents the expected range of compensation for this role:

  • The estimated base salary range for this role is $214,000 - $327,750.
  • Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.