Mlops Data Platform Intern, Automotive - 2026

MLOps Data Platform Intern

NVIDIA's Automotive division is building the next generation of AI and accelerated computing technologies for autonomous driving. Our MLOps Data Platform team designs large-scale data infrastructure powering Ground Truth (GT) generation, sensor fusion, and end-to-end AI workflows for global automotive partners. We are expanding our data platform globally to deliver GT data across regions and support diverse DNN networks for various OEMs.

We're looking for a motivated MLOps Data Platform Intern to help build, scale, and optimize this global data ecosystem while driving strong collaboration across engineering, operations, and research teams.

What You'll Be Doing:

1. Contribute to the development of distributed data pipelines supporting large-scale GT generation and global data distribution.
2. Support the integration of international datasets (vision, LiDAR, map, and sensor) for multi-region model development and validation.
3. Assist in automating workflows for data validation, QA, and release, improving throughput and reliability across global operations.
4. Collaborate with cross-functional teams (MLOps, MLE, Mapping, AI Research, Ops) to ensure consistent delivery of GT data worldwide.
5. Help design tools for monitoring data quality, job status, and progress tracking within the global GT release pipeline.
6. Participate in continuous improvement initiatives for platform scalability, performance tuning, and workflow automation.

What We Need to See:

• Currently pursuing a BS, MS, or PhD in Computer Science, Software Engineering, Data Engineering, or a related field.
• Solid programming experience with Python and C++.
• Understanding of distributed systems, data infrastructure, or cloud computing fundamentals.
• Analytical and problem-solving abilities, with an interest in large-scale AI data ecosystems.
• Good communication and teamwork skills, especially for collaboration across global and multi-disciplinary teams.

Ways to Stand Out from the Crowd:

• Proficient in using AI-assisted development tools (e.g., Cursor, Copilot) for programming productivity.
• Experience in data engineering, MLOps, or cloud-native workflow orchestration.
• Prior exposure to autonomous driving data, computer vision, or machine learning pipelines.
• Hands-on experience with project coordination, cross-region data delivery, or multi-team data operations.

At NVIDIA, interns are integral to real-world projects that push the boundaries of AI and data infrastructure. You'll gain hands-on experience in global-scale data operations, work with exceptional engineers, and play a role in enabling next-generation autonomous driving systems across the world.