2027 Summer Intern, AI Research, Embodied AI
About The Position
This internship is categorized as on-site, with the selected intern expected to report to the office 3 days a week. The Embodied AI Research team advances artificial intelligence methods for autonomous vehicles and embodied systems. We explore how models can combine visual and sensor understanding, language and other modalities, reasoning, prediction, and action to address challenging problems in autonomous driving. Our work includes 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. We work closely with engineering teams to translate research into reliable systems for real-world autonomy. As an Embodied AI Research Intern, you will conduct applied research on a well-scoped project at the intersection of machine learning, robotics, and autonomous driving. You will work with experienced researchers and engineers to develop hypotheses, design experiments, train and evaluate models, analyze results, and communicate findings. Potential focus areas include: Foundation Models for Autonomy, Vision-Language-Action Models, Generative and World Models, Learning for Planning and Control, and Multimodal and Temporal Learning.
Requirements
- Currently pursuing or in the process of obtaining a Ph.D. 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, with 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 venues may include 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
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
