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The Structured Perception team is dedicated to advancing the state-of-the-art in AI for autonomous vehicles, with a specific focus on structured perception outputs (online maps, object tracking capabilities, and handling long-tail scenarios). As an intern on the Structured Perception 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.
Job Responsibility:
Lead research and prototyping of advanced machine learning methods, such as ML track and map modules, foundation models, and vision-language architectures for real-world applications
Prototype ML models that improve perception, prediction, or decision-making for autonomous driving
Collaborate with cross-functional teams, including research, robotics, and systems engineering
Participate in technical discussions, share insights, and work towards publishing results
Requirements:
Currently pursuing or in the process of obtaining a Master’s or 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
Nice to have:
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
Graduating between December 2026 and June 2027
What we offer:
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
GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program