Job Description
To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.
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.
Locations:
San Francisco, California
Sunnyvale, California
Mountain View, California
About the Team :
The trajectory generation team (TGX) is responsible for turning scene understanding into wholistic AV behavior. The team must balance multiple competing objectives. Trajectories need to be comfortable for passengers (minimizing jerk and acceleration), obey traffic laws, respect vehicle dynamics constraints (steering limits, acceleration capabilities), avoid obstacles, and respond in real-time to changing road conditions. The TGX team uses state-of-the-art ML, RL, and optimization techniques to improve the GM driving product and support the objectives above.
About The Role:
As an intern on the trajectory generation team, you would work on well-scoped research or engineering projects that contribute to the team's ML-driven planning stack. This might involve implementing and benchmarking new neural network architectures for behavior prediction, improving data pipelines for training trajectory models, or conducting ablation studies on different learning approaches. The intern would collaborate closely with senior engineers and researchers, participating in code reviews, team meetings, and design discussions while gaining hands-on experience with production autonomous driving systems. They'd work with real-world driving data, simulation environments, and potentially see their contributions deployed to test vehicles.
The role offers a unique opportunity to bridge cutting-edge ML research with safety-critical robotics applications. An intern would develop skills in deep learning frameworks (PyTorch), work with large-scale distributed training systems, and learn how to validate and verify learned models for autonomous driving. Beyond technical skills, they'd gain insight into the challenges of building reliable AI systems for the real world-handling edge cases, ensuring safety guarantees, and balancing model performance with computational constraints. The experience provides exposure to how ML teams operate within a complex, multi-disciplinary engineering organization building toward full autonomy.
What You'll Do:
Implement and experiment with neural network architectures for trajectory prediction, behavior planning, or mission planning tasks
Build data pipelines and visualization tools to process, analyze, and evaluate large-scale driving datasets
Train and benchmark ML models using distributed compute infrastructure, running ablation studies tooptimizeperformance
Validate models in simulation environments and analyze failure cases across diverse driving scenarios
Participate in code reviews, team meetings, and technical discussions while documenting experiments and results
Contribute to production codebases by prototypingnew approachesfor handling challenging driving situations like merges or complex intersections
Required Qualification:
Currently enrolled in aPhD program in Computer Science, Machine Learning, Robotics, or a related STEM field.
Hands-on experience with one or more machine learning frameworks (e.g.,PyTorch, TensorFlow, JAX, orKeras).
Availability to work full-time (40 hoursper week) during the internship period.
Demonstrated coursework, research., or projects in AI/ML.
Strong programming skills in Python.
Preferred Qualifications:
Exposure todeep learning architectures such as Transformers, CNNs, or Diffusion Models.
Exposure todeep reinforcement learning algorithms such as PPO, DQL, and distributionaladaptations.
Experience with robotics through projects or research.
Familiarity with multimodal learning or working withcomplex, temporal data.
Interest in contributing to publications, open-source projects, or patents.
Familiarity with systems programming languages (e.g., C++ or Java) is a plus.
Intent to return todegree-programafter the completion of the internship.
Graduating between December 2026 and June 2027.
Compensation:
The monthly salary for this role is $13,100 per month
GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.
What you'll get from us (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
About GM
Our 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 Overview
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Non-Discrimination and Equal Employment Opportunities (U.S.)
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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 How we Hire (https://search-careers.gm.com/en/how-we-hire) .
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We are leading the change to make our world better, safer and more equitable for all through our actions and how we behave. Learn more about:
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Our Culture
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