MLOps Physical AI Data Intern - 2027

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.