Data Scaling Intern: AI Pipelines & Datasets (Hybrid)

General Motors LLC; Sunnyvale (CA); Hybrid; USD 132,000 - 163,000; Full time

Benefits offered by this job

Paid U.S. GM holidays

Mentorship and hands-on experience

Networking with company leaders

Job summary

General Motors LLC in Sunnyvale, CA seeks an Embodied AI Data Scaling Intern to help build data pipelines and tooling for large-scale autonomous driving datasets. You will collaborate with researchers and engineers to improve training workflows, conduct data quality analyses, and contribute to scalable data infrastructure.

The internship offers exposure to distributed training, dataset curation, and model-scale projects.

Qualifications

• Currently enrolled in or pursuing a Master’s or Ph.D. in CS/ML/DS/EE or related field.
• Demonstrated ML, data engineering, distributed systems experience via coursework, research, or projects.
• Strong Python programming and data-processing skills.

Responsibilities

• Develop data pipelines and tooling for large-scale autonomous driving datasets.
• Analyze data quality, coverage, distribution, and performance impacts using quantitative methods.
• Prototype and evaluate data mining, curation, labeling, sampling, or scenario discovery.
• Improve training throughput, data loading, experiment reproducibility, or distributed training workflows.
• Collaborate with ML researchers, data engineers, and autonomy teams.
• Build visualizations, metrics, dashboards, and evaluation workflows to communicate data and model behavior.
• Contribute to production-quality software through reviews, tests, CI, and documentation.

Skills

Python

Data analysis

Collaboration

Communication

Education

Master’s or Ph.D. in Computer Science / ML / Data Science / EE

Tools

PyTorch

TensorFlow

JAX

SQL

Data warehouses

Workflow orchestration

Distributed data-processing frameworks

Cloud infrastructure

GPU workflows

C++

Job description

General Motors LLC in Sunnyvale, CA seeks an Embodied AI Data Scaling Intern to help build data pipelines and tooling for large-scale autonomous driving datasets. You will collaborate with researchers and engineers to improve training workflows, conduct data quality analyses, and contribute to scalable data infrastructure.

The internship offers exposure to distributed training, dataset curation, and model-scale projects.