General Motors
Senior Machine Learning Perception Engineer - Fallback Driving System
$171K–$261K
GM Automation - Sunnyvale - GM Automation - Sunnyvale · Remote/Hybrid · Senior · Full-time · Posted Aug 4, 2026
- Experience
- 3–5 years developing ML solutions in perception, prediction, autonomous driving, or related domains.
- Education
- BS, MS, or PhD in Machine Learning, Robotics, Computer Science, or a related technical field; or equivalent practical experience building ML perception systems.
About the job
Develop and improve multimodal machine-learning perception models for Super Cruise 3’s fallback autonomy system, enabling a vehicle to reach a minimal risk condition when the primary system fails.
What you'll do
- Design, train, evaluate, and optimize models for detection, segmentation, tracking, and short-horizon prediction using camera, lidar, and radar data.
- Build and maintain training, inference, integration, and validation workflows for the fallback perception model.
- Collaborate across perception, planning, controls, safety, and systems teams; define metrics and support testing and technical mentorship.
What they ask for
- BS, MS, or PhD in Machine Learning, Robotics, Computer Science, or a related technical field; or equivalent practical experience building ML perception systems.
- Strong experience with multimodal sensor data, including preprocessing, synchronization, and fusion.
- Deep expertise in modern deep learning for perception, and proficiency in Python and at least one of PyTorch, TensorFlow, or JAX.
- Solid software engineering skills, including experience with C++ or similar languages.
Nice to have
- Experience deploying and optimizing ML models on embedded or resource-constrained platforms for real-time inference.
- Experience with AV/ADAS perception stacks, robotics, or ROS.
Pay
$170,600.00 to $261,300.00 USD base salary
Tools
camera, lidar, radar, PyTorch, TensorFlow, JAX, Python, C++
AI focus
Machine-learning perception for fallback autonomous driving, including object detection, segmentation, tracking, prediction, sensor fusion, and model optimization.
Model-written summary · the original posting is authoritative