Senior Machine Learning Engineer

General Motors

Sunnyvale, California, United States
Base: $170,000 to $240,000; bonus: incentive pyy p...
Fully remote
3+ years professional software engineering experience
2+ years specialized ai/ml infrastructure experience
Strong python programming skills with pytorch or tensorflow
This role involves designing scalable, reliable, and high-performance ML framework to support model training at scale for General Motors vehicles

Job Summary

  • This role involves designing scalable, reliable, and high-performance ML framework to support model training at scale for General Motors vehicles.
  • The successful candidate will collaborate with cross-functional teams to integrate new features and technologies into the platform while maximizing resource utilization.
  • General Motors offers a comprehensive benefits package including medical, dental, vision, retirement savings plans, and tuition assistance programs.

Matching Summary

This role involves designing scalable, reliable, and high-performance ML framework to support model training at scale for General Motors vehicles.

Salary

Base: $170,000 to $240,000; Bonus: Incentive pay program based on company and individual performance; Benefits: Medical, dental, vision, HSA, FSA, retirement plan, paid vacation, tuition assistance

Skills & Requirements

Must-have

  • 3+ years professional software engineering experience
  • 2+ years specialized AI/ML infrastructure experience
  • Strong Python programming skills with PyTorch or TensorFlow
  • Experience with distributed computing and GPU environments
  • Cloud environment experience (AWS, GCP, Azure)

Nice-to-have

  • Self-motivated impact-delivering oriented mindset
  • Extensive knowledge of PyTorch 2.x and distributed frameworks
  • Experience with FSDP and Pipeline Parallelism solutions
  • Proficiency in profiling and debugging training performance

Key Requirements

  • Bachelor's degree in Computer Science or equivalent experience
  • Willingness to travel to Sunnyvale, CA as needed
  • Comfortable working in highly ambiguous and dynamic environments

Work Rights

Not specified

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