2026 Summer Intern – AI/ML Intern – Model Scaling Foundations (Masters)
About The Position
About the Team: The Scaling Foundation s team is dedicated to building the ML technologies and cutting edge ML algorithms that enable us to go up the scaling curves for large driving models fo r building highly performant autonomous vehicles. We are a collaborative, forward-thinking group of researchers and engineers tackling some of the most complex challenges in autonomy and machine learning. About the Role: 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.
Requirements
- Currently pursuing or in the process of obtaining a Masters 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
Nice To Haves
- 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
Responsibilities
- 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.
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
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Number of Employees
5,001-10,000 employees
