설명
Work Arrangement:
Hybrid: This internship is categorized as on-site. The selected intern is expected to report to the office 3 days a week.
Location:
Sunnyvale, CA
About the Team
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.
About the Role
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: Develop or adapt large-scale models that learn useful representations and capabilities from diverse driving data.
- Vision-Language-Action Models: Explore architectures that connect multimodal perception and high-level reasoning with autonomous vehicle decisions and actions.
- Generative and World Models: Use generative techniques to model complex driving environments, improve scenario understanding, or support planning and simulation.
- Learning for Planning and Control: Apply imitation learning, reinforcement learning, or other learning methods to improve prediction, decision-making, and vehicle behavior.
- Multimodal and Temporal Learning: Build methods that reason over camera, lidar, radar, map, language, and time-series information.
What You’ll Do
- 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.
Required Qualifications
- 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.
Preferred Qualifications
- 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.
- Must be graduating between December 2027 and June 2028
Compensation:
- The monthly salary range for this role is $11,800 – $14,600 per month
- GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2027 Student Program.
What You’ll Get from Us
- 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
다양성 정보
General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다. 자세한 정보는 GM 채용 과정 안내를 참고하십시오.
공평한 취업 기회 선언 (미국)
General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다. 자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다.
숙소 (미국 및 캐나다)
General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.