About this role
• Contribute to the development and application of advanced machine learning techniques for robotic systems
• Apply 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 the development of next-generation automation and flexible production systems
• Support intelligent robotic systems in manufacturing
• Contribute to GM’s technical leadership through technical presentations, intellectual property, technical documentation, and publications
Requirements
Pursuing a master's or PhD in Machine Learning, Physical Robotics, Computer Science, or a closely related field from a leading universityMust be graduating between August 2026 and June 2027Able to work full-time, 40 hours per weekStrong academic and applied background in machine learningExperience training policies for grasping, manipulation, contact-rich assembly, or other robotic skillsStrong programming and system development skills in Python, C++, and PyTorch/TensorFlowU.S. Person required: U.S. citizen, U.S. permanent resident, asylee, or refugeeMust not require GM immigration sponsorship now or in the future, including H-1B, OPT, STEM OPT, CPT, TN, J-1, or other immigration supportPosition subject to export control restrictionsPreferred: experience with dexterous and multi-contact manipulationPreferred: experience with mobile manipulation in dynamic or unstructured environmentsPreferred: experience with learning-based control for contact-rich assemblyPreferred: experience with simulation-to-real transfer and data-efficient learningPreferred: experience with foundation-model-enabled robotics, vision-language-action models, transformer-based control architectures, world models, and generative AI methods for robot planning and executionPreferred: experience in industrial or automotive manufacturing environmentsPreferred: publication record in leading conferences such as ICRA, RSS, CoRL, or NeurIPSCore Competencies
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 applications in manufacturing and automation.
Highest-signal resume keywords
Machine LearningReinforcement LearningPython ProgrammingC++ ProgrammingDeep LearningATS Optimization Keywords
Hard Skills
Machine LearningReinforcement LearningImitation LearningDeep LearningGraspingDexterous ManipulationMobile ManipulationContact-Rich AssemblyForce-Sensitive OperationsSimulation-to-Real TransferIndustry Keywords
Robotic SystemsAutomationFlexible Production SystemsManufacturingTechnical DocumentationIntellectual PropertyTools & Technologies
PyTorchTensorFlow
Company:
General Motors
Level of experience (years):
Senior (5+ years of experience)
How to apply:
Please mention NLP People as a source when applying