NVIDIA is building the next generation of AI and advanced data technologies for Physical AI. Our MLOps GT team designs large-scale data infrastructure, LLM models and agents powering Ground Truth (GT) generation, and end-to-end AI workflows for global automotive and robotic partners. We're looking for a motivated MLOps Physical AI Data 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:
- Contribute to the development of distributed data pipelines supporting large-scale GT generation and global data distribution.
- Support the integration of international datasets (vision, LiDAR, map, and sensor) for multi-region model development and validation.
- Develop GT auto labeling, LLM models, and a variety of AI Agents for the global GT generation.
- Help design tools for monitoring data quality, job status, and progress tracking within the global GT release pipeline.
- 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++.
- Good understanding of computer vision, AI agent development, LLM and machine.
- 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 developing AI agents.
- Experience in Physical AI data engineering, or MLOps.
- Prior exposure to autonomous driving data, computer vision, or machine learning pipelines.
- Hands-on experience with Physical AI modeling, GT data processing.
At NVIDIA, interns are integral to real-world projects that push the boundaries of Physical AI. You’ll gain hands-on experience in global-scale data operations, work with exceptional engineers, scientists, and play a role in enabling next-generation autonomous driving systems across the world.