2026 Summer Intern – AI/ML Intern – Model Scaling Foundations (PhD)

GM-posted about 20 hours ago
Full-time • Intern
Hybrid • Sunnyvale, CA
5,001-10,000 employees
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As an AI/ML Engineering Intern on the Model Scaling Foundations 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, access to very large datasets of autonomous driving, collaboration with leading researchers and engineers, and mentorship from experienced AV researchers to grow your skills in the autonomous vehicle industry.

  • 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.
  • Work with very large datasets containing diverse road driving conditions and driving behaviors an d build our large driving models with these datasets.
  • Collaborate with cross-functional teams, including perception , robotics, and systems engineering.
  • Participate in technical discussions, share insights, and work towards publishing results.
  • 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.
  • Experience working with large datasets, running parallel
  • 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
  • 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
  • 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
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