Intern Jobs, Sunnyvale

About the Team

The Data Scaling team builds the data, machine learning, and infrastructure foundations that help Embodied AI models improve with scale. The team works across data collection, curation, mining, labeling, dataset quality, model inputs, distributed training, experiment workflows, and the systems that help researchers and engineers develop, evaluate, and deploy models more efficiently.

The work supports large-scale autonomous driving models and the wider Embodied AI flywheel. The team combines machine learning, data engineering, distributed systems, and software engineering to make high-quality, product-aligned driving data available for perception, planning, trajectory generation, and other autonomy capabilities.

About the Role

As an Embodied AI Data Scaling Intern, you will work on a well-scoped project that improves the scale, quality, efficiency, or reliability of data and model development for autonomous driving. You will work 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 focus areas include:

• Data Curation and Quality: Build methods to select, filter, balance, and validate large driving datasets that match product and modeling needs.
• Data Mining and Scenario Discovery: Find valuable, rare, or challenging driving situations and build tools to improve coverage of long-tail scenarios.
• Dataset and Labeling Pipelines: Improve automated labeling, data transformation, feature generation, and dataset release workflows.
• Distributed Training and Model Scaling: Optimize the systems, input pipelines, and compute workflows used to train large models on large datasets.
• ML Experimentation and Flywheel Infrastructure: Build tools that help teams develop, train, evaluate, debug, and deploy models more quickly and reliably.

What You Will Do

• 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 production-quality software through design reviews, code reviews, automated testing, continuous integration, and documentation.
• Present technical findings and document experiments, results, and recommendations.

What You Will Get

• 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.

About GM

GM's vision is a world with Zero Crashes, Zero Emissions and Zero Congestion. The company takes on the responsibility to lead the change that will make the world better, safer and more equitable for all.

GM wants every employee to feel they belong to one General Motors team, and it aims to drive meaningful change through its words, its actions and its culture.