This role pays more than
76%
of similar roles. Most pay
$151,000–$206,450
— the shaded band above.
At the midpoint, this role pays about
$216k
versus about
$179k
for comparable roles.
Based on 240 similar postings.
Employer
About General Motors (GM)
General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.
General Motors (GM) currently has
168 open roles
on FindRole.
Listed pay typically runs
$159,200–$245,000
across 60 roles with salary data.
Senior Software Engineer - Motion Planning, Secondary Driving System
As a Senior Software Engineer on the Secondary Driving System team within Embodied AI, you will serve as an individual contributor focused on motion planning and controls in a robotics context. You will develop production-grade C++ software to integrate ML-based perception, tracking, prediction, and analytical planners with classical controllers under strict latency constraints. Your work involves designing algorithms for lane-keeping, obstacle avoidance, and controlled stopping behaviors to ensure the vehicle reaches a minimal risk condition if primary systems fail. You will utilize C++, Python, and robotics middleware while collaborating on state estimation and vehicle dynamics. The role addresses the critical safety problem of maintaining vehicle operation during system failures by building robust, fail-operational behaviors for Super Cruise and future products, ensuring safe transitions to a minimal risk maneuver when necessary.
What does a Software Engineer earn in California?
Median $214000 from 925 postings across 71 companies.
Develop and optimize production-grade C++ software for motion planning and control systems under strict latency constraints.
Design algorithms for lane-keeping, obstacle avoidance, and controlled stopping behaviors for Minimal Risk Maneuver scenarios.
Integrate ML-based perception data with analytical planners and classical controllers to ensure safe vehicle operation.
Define and implement technical interfaces between state estimation, mapping, localization, and autonomy management systems.
Own features end-to-end from requirement clarification and design reviews through simulation, HIL testing, and on-road validation.
Debug complex integration issues using logs and telemetry to root-cause problems across perception, planning, and vehicle behavior.
Ensure all software designs align with functional safety requirements and fail-operational standards for advanced driving features.
Mentor other engineers through code reviews and design discussions to improve team execution and code quality.
What we're looking for
BS, MS, or PhD in Computer Science, Robotics, Electrical/Mechanical Engineering, or a related field (or equivalent practical experience).
3+ years of professional software engineering experience building production systems in robotics, autonomous vehicles, or complex real-time/control systems.
Strong proficiency in modern C++ (C++14/17 or later) and familiarity with Python for tooling and data analysis.
Experience in motion planning and controls, including trajectory generation, tracking, and optimal control or model-predictive control.
Experience in classical and modern feedback control design such as PID or LQR.
Experience integrating with perception and prediction pipelines including object detection, tracking, and road geometry.
Proven track record of delivering high-quality autonomous software under latency and compute constraints.
Background in ROS, safety-critical software, or GPU-based ML inference (preferred).
C++
Python
Control Theory
Trajectory Optimization
Motion Planning
Vehicle Dynamics
ROS
Numerical Optimization
Automated Testing
safety critical systems
Simulation
AV
ADAS
Motion Planning
Trajectory Optimization
Control Theory
Vehicle Dynamics
C++
Python
ROS
Numerical Optimization
Automated Testing
safety critical systems
Simulation
Systems Engineering
Motion Planning
Trajectory Optimization
Control Theory
Vehicle Dynamics
C++
Python
ROS
Numerical Optimization
Automated Testing
safety critical systems
C++
Python
Model Predictive Control
Trajectory Optimization
Motion Planning
Control Theory
Vehicle Dynamics
Robotics
ROS
Numerical Optimization
Simulation
Estimation
Prediction
ADAS