Staff Ml Engineer - Embodied Ai Offboard Perception

General Motors Australia & New Zealand

Austin, US
Base: $189,300.00 to $320,700.00; bonus/equity: in...
Hybrid
Machine learning solutions
Autonomous vehicle behavior
Object detection/tracking/classification
Develop and deploy offboard machine learning solutions that deliver ground-truth–quality world estimates for autonomous vehicle development

Job Summary

  • Develop and deploy offboard machine learning solutions that deliver ground-truth–quality world estimates for autonomous vehicle development.
  • Design and implement ML solutions using techniques such as unsupervised pre-training, supervised learning, and foundation modeling to solve complex problems.
  • Collaborate with cross-functional teams, shape technical direction, and mentor other engineers while transitioning research into scalable onboard ML capabilities.

Matching Summary

Develop and deploy offboard machine learning solutions that deliver ground-truth–quality world estimates for autonomous vehicle development.

Salary

Base: $189,300.00 to $320,700.00; Bonus/Equity: Incentive pay program based on company, job level, and individual performance; Benefits: Health and wellbeing benefits including medical, dental, vision, retirement savings plan, and more

Skills & Requirements

Must-have

  • Machine learning solutions
  • Autonomous vehicle behavior
  • Object detection/tracking/classification
  • Large-scale datasets
  • PyTorch and Python proficiency
  • ML model deployment
  • Applied research in ML

Nice-to-have

  • Human-centered design process
  • Cross-functional collaboration
  • Mentorship and knowledge sharing
  • Robotics or autonomous driving experience

Key Requirements

  • Master's or PhD in Computer Science, Robotics, Machine Learning, or related field
  • Experience with large-scale foundation models and alignment methods
  • Demonstrated ability to deliver applied ML solutions under real-world constraints
  • Experience building and scaling model training pipelines
  • Experience deploying ML models into production environments

Work Rights

Not specified

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