Job Description<div>  </div><div>To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.  </div><div>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.  </div><div>  </div><div>Locations:   </div><div>San Francisco, California  </div><div>Sunnyvale, California   </div><div>Mountain View, California   </div><div>  </div><div>About the Team: </div><div>The Sensor Encoder team is dedicated to advancing the state-of-the-art in AI for autonomous vehicles, with a specific focus on encoders for camera, lidar and radar. We are a collaborative, forward-thinking group of researchers and engineers tackling some of the most complex challenges in autonomy and machine learning related to sensor data processing. </div><div>  </div><div>About the Role:   As an intern on the sensor encoder 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.  </div><div>  </div><div>What You’ll Do:   </div><div><ul><li>Lead research and prototyping of advanced machine learning methods, such as foundation models, vision-language architectures, self-supervised learning. </li></ul></div><div><ul><li>Prototype ML models that improve perception, prediction, or decision-making for autonomous driving.  </li></ul></div><div><ul><li>Collaborate with cross-functional teams, including research, robotics, and systems engineering.  </li></ul></div><div><ul><li>Participate in technical discussions, share insights, and work towards publishing results.  </li></ul></div><div>  </div><div>Required Qualifications:   </div><div><ul><li>Currently pursuing or in the process of obtaining a Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field.  </li></ul></div><div><ul><li>Solid understanding of modern machine learning techniques, especially deep learning architectures (e.g., transformers, generative models, multimodal learning).  </li></ul></div><div><ul><li>Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.  </li></ul></div><div><ul><li>Research experience in AI/ML, demonstrated through coursework, academic projects, or publications.  </li></ul></div><div><ul><li>Strong problem-solving skills and a collaborative mindset.  </li></ul></div><div><ul><li>Strong communication and presentation skills.  </li></ul></div><div><ul><li>Experience working and communicating cross functionally in a team environment.  </li></ul></div><div><ul><li>Able to work fulltime, 40 hours per week  </li></ul></div><div>  </div><div>Preferred Qualifications:  </div><div><ul><li>Familiarity with autonomous vehicles or advanced driver assistance systems (ADAS).  </li></ul></div><div><ul><li>Experience working with large-scale datasets and training ML models in high-performance computing environments.  </li></ul></div><div><ul><li>Intent to return to degree program after the completion of the internship/co-op  </li></ul></div><div><ul><li>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.  </li></ul></div><div><ul><li>Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches  </li></ul></div><div><ul><li>Graduating between December 2026 and June 2027.  </li></ul></div><div>  </div><div>Compensation:   </div><div><ul><li>The monthly salary range for this role is $13,100 per month   </li></ul></div><div><ul><li>GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.  </li></ul></div><div>  </div><div>What you’ll get from us (Benefits):  </div><div><ul><li>Paid US GM Holidays  </li></ul></div><div><ul><li>GM Family First Vehicle Discount Program  </li></ul></div><div><ul><li>Result-based potential for growth within GM  </li></ul></div><div><ul><li>Intern events to network with company leaders and peers </li></ul></div>
About GMOur 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 OverviewFrom 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 <a href="#" rel="noopener noreferrer" target="_blank">Total Rewards resources</a>.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 <a href="#" rel="noopener noreferrer" target="_blank">How we Hire</a>.AccommodationsGeneral 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, <a href="#" rel="noopener noreferrer" target="_blank">email</a> 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.


General Motors’ vision is to create a world with Zero Crashes, Zero Emissions and Zero Congestion, and we have committed ourselves to leading the way toward this future. Today, we are in the midst of a transportation revolution, and we have the ambition, the talent and the technology to realize the safer, better and more sustainable world we want. As an open, inclusive company, we’re also creating an environment where everyone feels welcomed and valued for who they are. One team, where all ideas are considered and heard, where everyone can contribute to their fullest potential, with a culture based in respect, integrity, accountability and equality. Our team brings wide-ranging perspectives and experiences to solving the complex transportation challenges of today and tomorrow. 

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General Motors

General Motors, a leader in automotive innovation, seeks a hybrid PhD intern for AI/ML Sensor Encoder. We want a candidate with strong machine learning, Python, and research skills. You will develop ML models for autonomous vehicles, collaborate with experts, and contribute to cutting-edge projects. Benefits include paid holidays, vehicle discounts, growth opportunities, and intern networking events.

AI/ML Intern Sensor Encoder

Summary