Machine Learning for Robotics

General Motors•Warren, MI

1d•Hybrid

About The Position

General Motors is seeking a Staff Researcher in Machine Learning for Robotics to drive the development and deployment of advanced learning methods for intelligent robotic systems in manufacturing. This role requires deep technical expertise in machine learning combined with a proven ability to apply these methods to complex, real-world robotic challenges, enabling next-generation automation and flexible production systems.

Requirements

PhD in Machine Learning, Robotics, Computer Science, or a closely related field from a leading university, or a MS with 3+ years of experience.
Strong academic and applied background in machine learning, with demonstrated experience training policies for grasping, manipulation, contact-rich assembly, or other robotic skills.
Strong programming and system development skills (Python, C++, PyTorch/TensorFlow).

Nice To Haves

Experience with: Dexterous and multi-contact manipulation, Mobile manipulation in dynamic or unstructured environments, Learning-based control for contact-rich assembly, Simulation-to-real transfer and data-efficient learning, Foundation-model-enabled robotics, including vision-language-action models, transformer-based control architectures, world models, and emerging generative AI methods for robot planning and execution.
Experience in industrial or automotive manufacturing environments.
Publication record in leading conferences (e.g., ICRA, RSS, CoRL, NeurIPS) and/or strong patent portfolio.
Proven ability to lead technical initiatives and influence cross-functional teams.

Responsibilities

Lead the development and application of advanced machine learning techniques for robotic systems, including: Reinforcement learning (RL), Imitation learning and learning from demonstration, Deep learning methods for perception, planning, and control.
Apply learning-based approaches to challenging robotic domains, including: Grasping and dexterous manipulation, Mobile manipulation and coordinated motion, Contact-rich assembly and force-sensitive operations.
Design, implement, and validate machine learning solutions on physical robotic platforms, from concept to production.
Translate research innovations into scalable, production-ready capabilities for manufacturing environments.
Define technical direction and research roadmaps for learning-based robotics within GM.
Mentor junior researchers and engineers, elevating the overall team capability in AI-driven robotics.
Contribute to GM’s technical leadership through intellectual property, publications, and external technical engagement.