2026 Summer Intern – AI/ML Intern - Autonomous Vehicle Engineering (PhD) job opportunity at General Motors.

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General Motors 2026 Summer Intern – AI/ML Intern - Autonomous Vehicle Engineering (PhD)
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loacation Sunnyvale, California, United States of America, United States Of America
loacation Sunnyvale, Cal..........United States Of America

Job Description Work Arrangement:   Hybrid: This internship is categorized as   hybrid . The selected intern is expected to report to the office up to three times per week or as   determined   by the team.     Locations:    San Francisco, California   Sunnyvale, California    Mountain View, California      About the Team:   The AI Research organization is dedicated to advancing   the state -of-the- art   in AI for autonomous vehicles. We are a collaborative, forward-thinking group of researchers and engineers tackling some of the most complex challenges in autonomy and machine learning.     About the Role:   As an AI/ML Research Intern on the AI Research team,   you’ll   work on   cutting-edge   projects advancing vehicle autonomy, developing algorithms and models that shape the future of self-driving technology. This   internship provides experience with real-world AI/ML systems, collaboration with leading researchers and engineers, and mentorship from experienced AV researchers to grow your skills in the autonomous vehicle industry.     What   You’ll   Do:    Lead research and prototyping of advanced machine learning methods, such as foundation models, vision-language architectures, diffusion models, image/video generation, self-supervised learning, imitation learning, and reinforcement learning.   Prototype ML models that improve   perception , prediction, or decision-making for autonomous driving.   Collaborate with cross-functional teams, including   perception , robotics, and systems engineering.   Participate in technical discussions, share insights, and work towards publishing results.     Required Qualifications:    Currently pursuing or   in the process of obtaining   a   Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field.   Solid understanding of modern machine learning techniques, especially deep learning architectures (e.g., transformers, generative models, multimodal learning).   Proficiency   in Python and ML frameworks such as   PyTorch   or TensorFlow.   Research experience in AI/ML,   demonstrated   through coursework, academic projects, or publications.   Strong problem-solving skills and a collaborative mindset.   Strong communication   and presentation skills .   Experience working and communicating cross functionally in a team environment.   Able to work fulltime,   40 hours   per week     Preferred Qualifications:   Familiarity with autonomous vehicles or advanced driver   assistance   systems (ADAS).   Experience working with large-scale datasets and training ML models in high-performance computing environments.   Intent to return to degree program after the completion of the internship/co-op   Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as   NeurIPS , CVPR, ICML, ICLR, AAAI, ECCV, RSS, ICRA,   CoRL , or similar.   Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches   Experience building systems based on machine learning, reinforcement   learning   and/or deep learning methods     Compensation:    The monthly salary for this role is $13,100 per month    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 General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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