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Summer Intern – Research and Development – Machine Learning for Automation
General Motors. Develop and apply advanced machine learning techniques for robotic systems .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in advanced machine learning techniques, particularly in reinforcement learning, imitation learning, and deep learning for robotic systems. Proficient in programming with Python and C++, with a strong focus on developing intelligent robotic systems for manufacturing and automation.
Highest-signal resume keywords
Machine LearningReinforcement LearningPython ProgrammingC++ ProgrammingDeep Learning
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningReinforcement LearningImitation LearningDeep LearningGraspingDexterous ManipulationMobile ManipulationContact-Rich AssemblyTechnical DocumentationPublications
Tools & Technologies
PyTorchTensorFlow
Industry Keywords
Robotic SystemsIntelligent RoboticsAutomationFlexible Production SystemsManufacturing
Tech Stack
Tools & technologiesAssemblyPythonPyTorchTensorflowC++
About the role
Key responsibilities & impact- Develop and apply advanced machine learning techniques for robotic systems
- Work with reinforcement learning, imitation learning, learning from demonstration, and deep learning for perception, planning, and control
- Apply learning-based approaches to grasping, dexterous manipulation, mobile manipulation, coordinated motion, contact-rich assembly, and force-sensitive operations
- Contribute to GM’s technical leadership through technical presentations, intellectual property, technical documentation, and publications
- Support development and deployment of intelligent robotic systems for manufacturing
- Contribute to next-generation automation and flexible production systems
- Enable robots to learn, adapt, and perform complex manipulation, processing, and assembly tasks in real-world production environments
Requirements
What you’ll need- Pursuit of an advanced degree (Masters or PhD) in Machine Learning, Physical Robotics, Computer Science, or a closely related field from a leading university
- Strong academic and applied background in machine learning
- Experience training policies for grasping, manipulation, contact-rich assembly, or other robotic skills
- Strong programming and system development skills in Python, C++, and PyTorch/TensorFlow
- Must be a current student
- Able to work full-time, 40 hours per week during the summer months
- U.S. Person status required: U.S. citizen, U.S. permanent resident, asylee, or refugee
- Must not require GM immigration sponsorship now or in the future
- Position subject to export control restrictions
- Preferred: experience with dexterous and multi-contact manipulation; mobile manipulation; learning-based control for contact-rich assembly; simulation-to-real transfer; data-efficient learning; foundation-model-enabled robotics; industrial or automotive manufacturing environments; publications in leading conferences
Benefits
Comp & perks- One-time lump sum taxable stipend payment to eligible students selected for the 2027 Student Program to help facilitate relocation benefits
- Hybrid work arrangement
- Opportunity to contribute to leading industrial research and technical leadership
- Potential opportunities for technical presentations, intellectual property, technical documentation, and publication