Job Opportunities API

The Opportunity Want to work on the machine learning models that actually control robots? We're looking for an engineering student to join us on post-training our robot foundation models, starting with a 3-month internship and continuing as a working student (minimum 1 year total). This is a hands-on role at the core of our ML work. Together with the team, you'll help finetune large foundation models for robotics and improve the real-world performance of our control policies. You'll get to read recent papers, implement them in code, and apply them on real robots to see the results, and along the way you'll learn how large robot foundation models are trained, deployed, and improved. For the right person, this can also open up thesis topics down the line. Your Responsibilities Help optimize our fine tuning pipelines and improve the performance of our control policies. Read recent papers, help us implement them in code, and test them on real robots. Experiment with new post-training techniques for our models. Contribute to and improve our existing evaluation and benchmarking harnesses: compute metrics, compare model versions, and report what you find. Improve the tooling and workflows that make training and fine tuning jobs easier to start, configure, and debug. Automate recurring post-training work, such as hyperparameter and ablation sweeps.