General Motors
Senior Software Engineer - Motion Planning, Secondary Driving System
$171K–$261K
Sunnyvale, California, United States of America +3 · Remote/Hybrid · Senior · Full-time · Posted Oct 1, 2026
- Location
- Sunnyvale, California, United States of America
Remote - Washington
Austin, Texas, United States of America
Warren, Michigan, United States of America - Experience
- 3+ years of professional software engineering experience building production systems in robotics, autonomous vehicles, or complex real-time/control systems.
- Education
- BS, MS, or PhD in Computer Science, Robotics, Electrical/Mechanical Engineering, or a related field; or equivalent practical experience.
About the job
Build production software for GM’s Secondary Driving System, focusing on motion planning and controls that safely manage vehicle operation and minimal-risk maneuvers when the primary driving system fails.
What you'll do
- Develop and optimize C++ software across the autonomy stack, integrating perception with planners and controllers.
- Design planning and control algorithms for lane keeping, obstacle avoidance, lane changes, and controlled stopping.
- Own features from requirements and design through testing, simulation, on-road validation, and iteration.
What they ask for
- BS, MS, or PhD in a related field, or equivalent practical experience.
- 3+ years building production systems in robotics, autonomous vehicles, or complex real-time/control systems.
- Proficiency in modern C++ and familiarity with Python.
- Experience in motion planning and controls, perception/prediction integration, and delivering reliable autonomous or robotics software.
Nice to have
- Background in ROS or similar robotics middleware; experience with safety-critical software or functional safety teams.
- Hands-on experience with GPU/accelerator-based ML inference and production model deployment.
Pay
$170,600.00 to $261,300.00 USD base salary
Tools
C++14/17, Python, ROS, GPU/accelerator-based ML inference, PID, LQR
AI focus
Integrate ML-based perception, tracking, and prediction with motion planning and controls for an autonomous driving safety system.
Model-written summary · the original posting is authoritative