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Machine Learning for Robotics

  • 위치
    • Warren, Michigan
  • 직무 유형 Full time
  • 게시됨
  • Job Requisition JR-202607217

설명

JR-202607217

Job Title: Staff Researcher – Machine Learning for Robotics

Role Overview

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.

Key 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

Required Qualifications

  • 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)

Preferred Qualifications

  • 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

Staff-Level Expectations

  • Demonstrated experience in project leadership, taking project(s) from initiation through implementation.
  • Acts as a subject matter expert in machine learning for robotics across GM
  • Drives the application of AI to high-impact manufacturing problems
  • Balances cutting-edge research with robustness, safety, and scalability requirements for production deployment

Impact

This role will help shape the future of intelligent automation at GM by enabling robotic systems capable of learning, adapting, and performing complex manipulation and assembly tasks in real-world production environments—unlocking new levels of flexibility, efficiency, and capability in manufacturing.

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

이 직무는 하이브리드 직무로 분류됩니다. 즉, 선발된 지원자는 특정 근무지로 주 3일 이상(또는 관리자가 지정한 다른 빈도로) 특정 근무지로 출근해야 합니다.

이 직무는 리로케이션 혜택을 받을 수 있습니다.

다양성 정보

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공평한 취업 기회 선언 (미국)

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숙소 (미국 및 캐나다)

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