2027 Summer Intern, Data Scaling, Embodied AI (Masters)

General Motors • Sunnyvale, CA

1d • Hybrid

About The Position

The Data Scaling team builds data, machine learning, and infrastructure foundations that enable Embodied AI models to improve with scale. Its work spans data collection, curation, mining, labeling, dataset quality, model inputs, distributed training, experiment workflows, and systems that help researchers and engineers develop, evaluate, and deploy models more efficiently. The team supports large-scale autonomous driving models and the broader Embodied AI flywheel, combining machine learning, data engineering, distributed systems, and software engineering to provide high-quality, product-aligned driving data for autonomy capabilities.

As an Embodied AI Data Scaling Intern, you will work on a well-scoped project to improve the scale, quality, efficiency, or reliability of data and model development for autonomous driving. You will collaborate with researchers and engineers to build data pipelines, analyze large datasets, improve training workflows, or develop infrastructure that increases the number and quality of experiments the team can run. Potential projects include data curation and quality, data mining and scenario discovery, dataset and labeling pipelines, distributed training and model scaling, and ML experimentation and flywheel infrastructure.

This is a hybrid internship categorized as on-site. The selected intern is expected to report to the Sunnyvale, California office three days per week. The intern must be available to work full-time, 40 hours per week, during the internship period.

Requirements

• Currently enrolled in or pursuing a Master's degree in Computer Science, Machine Learning, Data Science, Electrical Engineering, or a related technical field.
• Demonstrated experience through coursework, research, academic projects, or professional work in machine learning, data engineering, distributed systems, or a related area.
• Strong programming skills in Python.
• Experience working with data processing, databases, machine learning pipelines, or large-scale datasets.
• Strong analytical and problem-solving skills, with the ability to use quantitative analysis to guide decisions.
• Ability to work collaboratively in a cross-functional, team-oriented environment.
• Strong written, verbal, and presentation skills.
• Availability to work full-time, 40 hours per week, during the internship period.
• Must be graduating between December 2027 and June 2028.
• Intent to return to a degree program after completion of the internship.

Nice To Haves

• Experience with PyTorch, TensorFlow, JAX, or another machine learning framework.
• Experience with distributed training, parallel computing, high-performance computing, cloud infrastructure, or GPU-based workflows.
• Familiarity with multimodal sensor data, autonomous vehicles, robotics, computer vision, or large-scale time-series data.
• Experience with SQL, data warehouses, workflow orchestration, data quality systems, or distributed data-processing frameworks.
• Familiarity with foundation models, self-supervised learning, imitation learning, reinforcement learning, or deep learning.
• Experience with C++ or another systems programming language.

Responsibilities

• Develop data pipelines and tooling for large-scale, multimodal autonomous driving datasets.
• Analyze data quality, coverage, distribution, and performance impact using quantitative methods.
• Prototype and evaluate approaches for data mining, curation, labeling, sampling, or scenario discovery.
• Improve training throughput, data loading, experiment reproducibility, or resource utilization in distributed computing environments.
• Collaborate with machine learning researchers, data engineers, infrastructure engineers, and autonomy teams.
• Build visualizations, metrics, dashboards, and evaluation workflows to communicate data and model behavior.
• Contribute to production-quality software through design reviews, code reviews, automated testing, continuous integration, and documentation.
• Present technical findings and document experiments, results, and recommendations.

Benefits

• Paid U.S. GM holidays.
• GM Family First Vehicle Discount Program.
• Potential for growth within GM based on performance and business needs.
• Intern events and opportunities to network with company leaders and peers.
• Mentorship and hands-on experience with the data and ML foundations behind autonomy.
• One-time lump sum taxable stipend payment for eligible students selected for the 2027 Student Program.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern