Job Description

The AI Research team is advancing how intelligent robotic systems perceive, act, and adapt in the physical world. We are pioneering the next generation of embodied AI—integrating multimodal foundation models, robot learning architectures, and real-world deployment to solve manipulation, planning, and simulation challenges at an industrial scale.

As a Robotics Engineer Intern, you will lead the development of end-to-end AI systems that enable dexterous manipulation, autonomous behaviors, and multimodal understanding on physical robotic platforms. You will design, prototype, and implement cutting-edge models spanning perception, policy learning, 3D reasoning, and control—working closely with robotics engineers, AI infrastructure teams, and production partners to bring research into deployment.

What You’ll Do

• Design and implement advanced robot learning architectures (e.g., diffusion policies, ACT, VLM/VLA agents, imitation learning) to support manipulation, path planning, and autonomous execution.

• Build end-to-end model training pipelines for robotics applications, integrating multi-modal sensor data such as RGB, depth, force/torque, LiDAR, and proprioceptive signals.

• Develop scalable policy inference and control loops, pairing high-level perception with motion planning and on-robot execution.

• Apply or extend large-scale architectures—LLMs, VLMs, VLAs, diffusion models—to embodied tasks, sim-to-real adaptation, and grounding.

• Collaborate with cross-functional teams to translate research prototypes into deployable robotics software, ensuring robustness, efficiency, and safety.

• Design data collection, demonstration strategies, and simulation frameworks to support offline training, imitation learning, and hardware validation.

• Stay current with state-of-the-art advancements in embodied AI, robot learning, and manipulation, and share findings through internal research discussions and presentations.

Required Qualifications

• Pursuing a PhD in a relevant STEM field (e.g., Computer Science, Electrical/Mechanical Engineering, Robotics, or related discipline), or pursuing a Master’s degree with equivalent industry experience in applied robotics or robot learning with a planned graduation date between December 2026 - June 2027.

• Proven experience in building and deploying ML models on robotic systems—including training, evaluation, and integration with real or simulated platforms.

• Deep understanding of modern AI architectures (e.g., Transformers, VLMs/VLAs, diffusion models, CNNs) and hands-on experience training models at scale.

• Strong implementation ability in Py Torch, including writing custom modules, batching, debugging, and performance/efficiency considerations.

• Practical experience with ROS/ROS2 or robotics middleware and integrating learning components into manipulation or motion-control workflows.

• Demonstrated research impacts through robotics/ML publications or contributions to production-grade robotics systems.

• Ability to translate ambiguous embodied AI problems into well-scoped experiments, and maintain rigorous evaluation, ablation, and statistical validation practices.

Preferred Qualifications

• Experience developing robot learning systems for manipulation, motion planning, or autonomous behaviors (e.g., diffusion policies, ACT, behavioral cloning, offline RL).

• Hands-on expertise with robotics perception, including 3D understanding, depth/RGB fusion, multimodal grounding, or force/torque sensing.

• Familiarity with simulation environments such as Isaac Sim, Mujoco, Gazebo, or Py Bullet, and demonstrated experience with sim-to-real transfer strategies.

• Working knowledge of robotics middleware (ROS/ROS2) and integration of ML components into real-time robotic stacks.

• Experience building or adapting foundation models for embodied tasks (VLMs/VLAs, multimodal diffusion, instruction-following agents).

• Track record of production-ready robotics systems, open-source contributions, or publications in top-tier robotics/AI venues.

Why Join Us

You’ll be part of a mission-driven team transforming how AI interacts with the physical world. This role offers the opportunity to design foundational robotic learning models, collaborate with world-class experts, and see your innovations deployed on real robotic systems across GM’s global ecosystem.

Location: This role is categorized as hybrid. This means the successful candidate is expected to report to the MTV office three times per week or any other frequency dictated by the business.

Compensation:

• The monthly salary range for this role is $9,100 - $ 13,100 dependent upon class status and degree.

• GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.

What you’ll get from us (Benefits):

• Paid US GM Holidays

• GM Family First Vehicle Discount Program

• Result-based potential for growth within GM

• Intern events to network with company leaders and peers

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-Discrimination 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.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

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