Staff Ml Engineer - Embodied Ai Onboard Autonomy

General Motors Australia & New Zealand

Mountain View, California, United States
Base: $180,000 to $280,000; bonus: incentive pyy b...
Hybrid
End-to-end ml model deployment
Real-time inference optimization
Python and c++ proficiency
General Motors is seeking a Staff ML Engineer for their Embodied AI team, focusing on developing machine learning solutions for autonomous driving. The position emphasizes designing and deploying advanced ML models to enhance vehicle behavior in real-world scenarios, requiring significant experience in machine learning, computer vision, and software engineering

Job Summary

  • This role involves designing and deploying advanced onboard ML models that translate raw sensor data into actionable driving behaviors for autonomous vehicles.
  • Candidates will lead critical technical initiatives, mentor ML engineers, and shape the future of onboard ML capabilities within a collaborative team.
  • The position offers a competitive salary range of $180,000 to $280,000, bonus potential, and eligibility for a company vehicle evaluation program.

Matching Summary

Match Score: 85

General Motors is seeking a Staff ML Engineer for their Embodied AI team, focusing on developing machine learning solutions for autonomous driving. The position emphasizes designing and deploying advanced ML models to enhance vehicle behavior in real-world scenarios, requiring significant experience in machine learning, computer vision, and software engineering.

Salary

Base: $180,000 to $280,000; Bonus: Incentive pay based on performance; Benefits: Company vehicle program available

Skills & Requirements

Must-have

  • End-to-end ML model deployment
  • Real-time inference optimization
  • Python and C++ proficiency
  • Deep learning architecture design
  • Computer vision expertise

Nice-to-have

  • AV/ADAS experience preferred
  • Mentoring junior engineers
  • Cross-functional collaboration
  • Strategic roadmap influence

Key Requirements

  • Master's or Ph.D. in Machine Learning or related field
  • 4+ years experience with large-scale Foundation Models
  • Proven track record in safety-critical deep learning systems

Work Rights

Not specified

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