2026 Summer Intern - Machine Learning Engineer- Autonomous Vehicle Engineering (PhD) job opportunity at General Motors.

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General Motors 2026 Summer Intern - Machine Learning Engineer- Autonomous Vehicle Engineering (PhD)
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Pattern: full-time
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degreePhD
loacation Sunnyvale, California, United States of America, United States Of America
loacation Sunnyvale, Cal..........United States Of America

Job Description To help   facilitate   administration of relocation benefits if you are selected, please apply using the permanent address you would move from.   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.     Location:   Sunnyvale, California     About the Team:   Offboard   perception : Unlike onboard   perception , which must run in real time on the AV, offboard   perception   can   leverage   larger models, greater compute, and acausal processing to achieve much higher accuracy. These high-accuracy detections support multiple consumers across the organization—for example, powering simulation and generating automated labels used to train onboard models.     About the Role:    As a Machine Learning Engineering Intern, you will work alongside a world-class team of engineers and researchers on impactful AI/ML projects in robotics and advanced manufacturing.   You’ll   gain hands-on experience contributing to the design, prototyping, and potential deployment of AI systems in real-world industrial settings. This is an excellent opportunity to explore applied research and development while learning from top experts in the field.     What   You’ll   Do:   Collaborate with cross-functional teams to adapt and   optimize   machine learning models for autonomous vehicle perception, including robotics and computer vision applications.   Help build and test components of end-to-end deep learning pipelines that process multimodal sensor data (e.g., cameras, lidars, radars).   Assist   in developing and evaluating foundation models and transfer learning techniques for use    Participate in translating technical and business requirements into ML prototypes.   Gain exposure to the training, deployment, and performance monitoring of machine learning models in production-like environments.   Learn how research ideas evolve into real-world applications and contribute to the team's   innovation   roadmap.     Required Qualifications:    Currently enrolled in a   PhD program in Computer Science, Machine Learning, Robotics, or a related STEM field.   Availability to work full-time ( 40 hours   per week) during the internship period.   Demonstrated coursework, research., or projects in AI/ML.   Strong programming skills in Python.   Able to work   fulltime ,   40 hours   per week.     Preferred Qualifications:   Exposure to   deep learning architectures such as Transformers, CNNs, or Diffusion Models.   Hands-on experience with one or more machine learning frameworks (e.g.,   PyTorch , TensorFlow, JAX, or   Keras ).   Experience with robotics, computer vision through projects or research.   Familiarity with multimodal learning or working with sensor data.   Interest in contributing to publications, open-source projects, or patents.   Familiarity with systems programming languages (e.g., C++ or Java) is a plus.   Intent to return to   degree-program   after the completion of the internship.   Graduating between December 2026 and June 2027.     Compensation:   The monthly salary range 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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