MLOps Physical AI Data Intern - 2027
At a glance
Junior ML Platform & Ops role at NVIDIA. China, Shanghai · full-time.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build distributed data flows for large Ground Truth generation and send the resulting data to global destinations
- Combine vision, LiDAR, map and sensor sources so models can be developed and checked across regions
- Create automated labeling, language models and AI agents to support global Ground Truth production
- Develop pipeline tools that surface data quality, job status and release progress
- Tune platform performance and scale while automating recurring workflows
What you bring
- You are working toward a bachelor’s, master’s or doctoral degree in computer science, software or data engineering, or a related field
- You have solid programming ability in both Python and C++
- You understand computer vision, AI agent development and language models
- You bring analytical problem-solving skills and communicate well with global, multidisciplinary teams
Who this fits
This internship suits a student seeking practical work on large-scale AI data workflows. You’ll collaborate with engineering, operations and research teams across global projects.
From the employer
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.