General Motors is looking to solve the problem of advancing automation in manufacturing by developing and deploying robotic foundation models, which are multi-modal, scalable AI systems enabling generalizable perception, planning, and manipulation across diverse robotic platforms.
Requirements
- ML model development, deployment, and refinement* , especially in robotics or autonomous systems
- Foundation models* , LLMs, ViTs, and multi-modal architectures
- Python/C++ and ML frameworks like PyTorch, TensorFlow
- 3D vision, graphics pipelines, and robotic data modalities
- Robotics frameworks (ROS/ROS2, MoveIt, Nav2)
- CI/CD pipelines and modern software development practices such as Bash, Github, Bazel, Docker
- Publications in top-tier venues (e.g., NeurIPS, CVPR, ICRA, RSS)
Responsibilities
- Lead the development and deployment of robotic foundation models* , including vision-language-action (VLA) systems, reinforcement learning agents, and sim2real adaptation pipelines
- Architect scalable model training and inference systems* , ensuring robustness, efficiency, and real-world applicability
- Drive hands-on experimentation and refinement* , validating models in simulation and on physical embodiments across diverse tasks
- Collaborate with hardware and software teams* to integrate models into production-grade robotic systems
- Publish and patent* breakthrough research, contributing to GM’s intellectual property and academic presence
- Architecting and implementing advanced AI/ML systems
- Guiding strategic initiatives that push the boundaries of robotic autonomy
Other
- This is a staff technical leadership role
- Mentoring scientists and engineers
- Mentor and guide cross-functional teams* , fostering technical excellence and knowledge sharing across ARC
- Proven track record of technical leadership and cross-functional collaboration
- This role is categorized as onsite. This means the selected candidate is expected to report to a specific location on a full-time basis.
