Machine Learning Intern

Contribute to training runs: Work alongside founding engineers on world model or eval model experiments end-to-end

Run real-robot evaluations: Collect demonstration data, run policies on physical hardware, and document failure modes

Build tooling: Write Python and PyTorch code that improves our data engine, training pipelines, or eval infrastructure

Close the sim-to-real gap: Run experiments that test how well simulation predicts real-robot behavior

Experience with real robot hardware or simulation environments (Isaac, MuJoCo, etc.)

Prior research in manipulation, 3D vision, or model evaluation