Staff Software Engineer, Autonomy Evaluation

General Motors

Atlanta, Georgia, United States
Base: $185,100 - $284,100; bonus: incentive pyy ba...
Fully remote
7+ years robotics or autonomous systems experience
3+ years leading evaluation of complex dynamic systems
Proficiency in python production environments
The Evaluation team builds and evolves the ecosystem that powers developing and scaling GM's autonomous driving technology

Job Summary

  • The Evaluation team builds and evolves the ecosystem that powers developing and scaling GM's autonomous driving technology.
  • You will define the strategy and architecture for metrics and analyses to evaluate autonomous driving software performance across the autonomy stack.
  • Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program.

Matching Summary

The Evaluation team builds and evolves the ecosystem that powers developing and scaling GM's autonomous driving technology.

Salary

Base: $185,100 - $284,100; Bonus: Incentive pay based on company and individual performance; Benefits: Medical, dental, vision, HSA, FSA, retirement plan, paid vacation, tuition assistance

Skills & Requirements

Must-have

  • 7+ years robotics or autonomous systems experience
  • 3+ years leading evaluation of complex dynamic systems
  • Proficiency in Python production environments
  • Strong ability working with large C++ autonomy codebases
  • Proven cross-team technical leadership

Nice-to-have

  • Experience designing large-scale simulation experiments
  • Deep familiarity with statistical modeling and hypothesis testing
  • Proficiency in C++ and SQL for data pipelines
  • Experience with ROS or robotics stack logging
  • Background in computational geometry and linear algebra

Key Requirements

  • PhD, Masters, or Bachelor's degree in Computer Science, Robotics, Engineering, or Machine Learning
  • 7+ years applied experience with robotics or autonomous systems software
  • 3+ years leading evaluation using numerical and ML approaches
  • No immigration sponsorship provided

Work Rights

Not specified

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