Internship

What you'll do

• Complete a scoped project in an area such as ML Performance, AI Infrastructure, ML Operations, Data, Robotics, Simulation, or World Models.
• Work in the team’s repositories, clusters, and data, and ship an artifact such as a dataset, benchmark, evaluation, or tool.
• Write up findings and recommended next steps.

What they ask for

• Bachelor’s degree or equivalent hands-on experience in Computer Science, Engineering, or a related technical field, or currently working toward one.
• Depth in machine learning fundamentals or systems fundamentals.
• Fluent Python skills and experience building and debugging a non-trivial system end to end independently.
• Identify a preferred project area and concretely describe what you would build or measure.

Nice to have

• Experience with scalable data pipelines, training infrastructure, simulation tooling, GPU kernels, physics engines, or real robot hardware.
• Research contributions on generative models or robot learning; open-source contributions or evidence of self-directed technical work.

Tools

Python, Megatron-Core, Isaac Lab, Ray Data, CUDA, Triton, MuJoCo, Newton

AI focus

Work on multimodal foundation world models for Physical AI, with internship projects potentially involving machine learning, robotics, simulation, or world models.