2026 Summer Intern – AI/ML Intern – Structured Perception (PhD)

General Motors • Full-time • United States • 2w ago

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 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). 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 perceiving the environment around the car and enabling responses to those.

About the Role:
As an intern on the Structurer 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.

What You’ll Do:

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.

Required Qualifications:

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

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.