Entry-Level - AI and Machine Learning for Automation Researcher

General Motors

Warren (MI)

Hybrid

USD 41,000 - 55,000

Full time

2 days ago
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Job summary

General Motors in Warren, MI is seeking a Summer Intern Researcher in Machine Learning for Automation to help develop and deploy advanced learning methods for intelligent robotic systems in manufacturing. You will work on RL, imitation learning, and deep learning for perception, planning, and control to support next-generation automation and flexible production.

You will contribute to GM's technical leadership through presentations, documentation, and publications, while collaborating with a

Qualifications

  • Pursuing a masters or PhD in ML, physical robotics, CS, or related field.
  • Graduating between August 2026 and June 2027.
  • Able to work fulltime, 40 hours per week.
  • Strong ML background with experience in grasping, manipulation, or related robotic skills.
  • Strong programming skills in Python and C++, with PyTorch/TensorFlow experience.

Responsibilities

  • Develop and apply advanced ML techniques for robotic systems.
  • Advance learning methods for perception, planning, and control.
  • Contribute to technical leadership through documentation and publications.

Skills

Machine learning
Robotics
Python
C++
PyTorch
TensorFlow
Reinforcement learning
Imitation learning
Deep learning

Education

Masters or PhD in ML/Robotics/CS
Graduating Aug 2026 - Jun 2027

Tools

Python
C++
PyTorch
TensorFlow

Job description

Job Description
The Role:

General Motors is seeking a Summer Intern Researcher in Machine Learning for Automation to make meaningful contributions towards driving the development and deployment of advanced learning methods for intelligent robotic systems in manufacturing. This role requires deep technical expertise in machine learning and physical robotics combined with a desire to apply these methods to complex, real-world robotic challenges, supporting the development of next-generation automation and flexible production systems.

What You'll Do:

Make meaningful contributions in the development and application of advanced machine learning techniques for robotic systems, which may include:

  • Reinforcement learning (RL)
  • Imitation learning and learning from demonstration
  • Deep learning methods for perception, planning, and control

Make meaningful contributions in the application of learning-based approaches to challenging robotic domains, including:

  • Grasping and dexterous manipulation
  • Mobile manipulation and coordinated motion
  • Contact-rich assembly and force-sensitive operations

Make meaningful contributions to GM's technical leadership as appropriate through technical presentations, intellectual property, technical documentation, and publication.

Required 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, 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)

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).

The position is subject to export control restrictions and requires the successful candidate to be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee or refugee).

Work Arrangement:

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI three times per week, at minimum [or other frequency dictated by the business].

To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources .

Non-Discriminator and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

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