2027 Summer Intern, AI Research, Embodied AI (Masters)

GM • Sunnyvale, CA

4d • Hybrid

About The Position

The Embodied AI Research Intern will conduct applied research on a well-scoped project at the intersection of machine learning, robotics, and autonomous driving. Working with experienced researchers and engineers, the intern will develop hypotheses, design experiments, train and evaluate models, analyze results, and communicate findings. Possible research areas include foundation models for autonomy; vision-language-action models; generative and world models; learning for planning and control; and multimodal and temporal learning across camera, lidar, radar, map, language, and time-series information.

The Embodied AI Research team advances artificial intelligence methods for autonomous vehicles and embodied systems, exploring how models combine visual and sensor understanding, language and other modalities, reasoning, prediction, and action. Its work spans foundation models, vision-language and vision-language-action architectures, generative and world models, self-supervised learning, imitation learning, reinforcement learning, multimodal learning, and methods for learning from large-scale driving data. The team collaborates with engineering teams to translate research into reliable systems for real-world autonomy.

This is a hybrid internship categorized as on-site. The selected intern is expected to report to the Sunnyvale, California office three days a week. The internship requires availability to work full-time, 40 hours per week, during the internship period. Candidates must be graduating between December 2027 and June 2028 and intend to return to a degree program after the internship or co-op.

Requirements

• Currently pursuing or in the process of obtaining a master's degree in Machine Learning, Artificial Intelligence, Computer Science, Robotics, or a related technical field.
• Strong understanding of modern machine learning and deep learning methods.
• Proficiency in Python and experience with PyTorch, TensorFlow, JAX, or another machine learning framework.
• Demonstrated AI/ML research experience through coursework, academic projects, publications, or comparable work.
• Strong analytical and problem-solving skills, including experience designing experiments and interpreting results.
• Ability to work collaboratively in a cross-functional, team-oriented environment.
• Strong written, verbal, and presentation skills.
• Availability to work full-time, 40 hours per week, during the internship period.
• Must be graduating between December 2027 and June 2028.

Nice To Haves

• Experience with transformers, large language models, vision-language models, vision-language-action models, diffusion models, or other generative architectures.
• Experience with reinforcement learning, imitation learning, self-supervised learning, world models, multimodal learning, or temporal modeling.
• Familiarity with autonomous vehicles, advanced driver assistance systems, robotics, or embodied AI.
• Experience working with large-scale datasets, distributed training, high-performance computing, or model scaling.
• Evidence of significant technical results through first-authored publications, grants, fellowships, patents, or open-source contributions.
• Relevant publications or work at venues such as NeurIPS, CVPR, ICML, ICLR, AAAI, ECCV, RSS, ICRA, CoRL, or similar conferences and workshops.
• Experience with C++ or another systems programming language.
• Intent to return to a degree program after completion of the internship or co-op.

Responsibilities

• Formulate research problems and develop prototypes for autonomous driving applications.
• Design and run experiments, ablation studies, and quantitative evaluations.
• Train and benchmark models using large-scale datasets and distributed compute infrastructure.
• Analyze model behavior, failure cases, generalization, and performance tradeoffs.
• Collaborate with perception, planning, robotics, controls, and systems engineering teams.
• Contribute to technical discussions, research documentation, publications, patents, or open-source work where appropriate.
• Present findings clearly to technical and cross-functional audiences.

Benefits

• Paid U.S. GM holidays.
• GM Family First Vehicle Discount Program.
• Potential for growth within GM based on performance and business needs.
• Intern events and opportunities to network with company leaders and peers.
• Mentorship and hands-on experience with the data and ML foundations behind autonomy.
• One-time lump sum taxable stipend payment for eligible students selected for the 2027 Student Program.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern