Hybrid AI & Robotics Research Intern – Automation

General Motors Corporation; Warren (MI); Hybrid; USD 34,000 - 48,000; Full time

Job summary

General Motors is seeking a Summer Intern Researcher in Machine Learning for Automation to advance learning methods for intelligent robotic systems in manufacturing. The role blends ML with real-world robotics challenges and requires strong Python/C++ and PyTorch/TensorFlow skills.

You will work hybrid in Warren, MI, contributing to grasping, manipulation, and mobile/contact-rich robotics, with opportunities to publish and present findings to GM leadership.

Qualifications

• Pursuing a masters or PhD in Machine Learning, Physical Robotics, Computer Science, or a closely related field from a leading university.
• Must be graduating between August 2026 - June 2027.
• Able to work fulltime, 40 hours per week.
• Strong academic and applied background in machine learning, with experience training policies for grasping, manipulation, or other robotic skills.
• Strong programming and system development skills (Python, C++, PyTorch/TensorFlow).

Responsibilities

• Make meaningful contributions in the development and application of advanced ML techniques for robotic systems.
• Apply RL, imitation learning, and deep learning for perception, planning, and control in manufacturing robots.
• Contribute to technical leadership through presentations, documentation, and publications.

Skills

Machine learning

Reinforcement learning

Imitation learning

Python

C++

PyTorch

TensorFlow

Robotics

Education

Masters or PhD in Machine Learning / Robotics / CS

Tools

PyTorch

TensorFlow

Simulation tools

Job description

General Motors is seeking a Summer Intern Researcher in Machine Learning for Automation to advance learning methods for intelligent robotic systems in manufacturing. The role blends ML with real-world robotics challenges and requires strong Python/C++ and PyTorch/TensorFlow skills.

You will work hybrid in Warren, MI, contributing to grasping, manipulation, and mobile/contact-rich robotics, with opportunities to publish and present findings to GM leadership.