Founding Research Engineer, Robot Learning

About the Role

Join a robotics data infrastructure startup as its first robot learning hire. You will train robot policies on synthetic data, rigorously measure their impact, and turn experimental results into public findings and practical data requirements. You will work closely with engineering and product teams across San Francisco and Paris, and help build the Bay Area robotics team.

What You'll Do

• Train and fine-tune robot policies using imitation learning, diffusion policies, vision-language-action models, or reinforcement learning in simulation.

• Run controlled evaluations on manipulation and grasping tasks, comparing results against baselines while holding seeds and protocols consistent.

• Report what improved and what did not, and use evaluation findings to guide the next data and simulation iterations.

• Write data specifications that define what to generate, including fidelity and variation requirements.

• Publish and demonstrate results to the robotics community, and contribute to customer technical discussions.

• Begin as an individual contributor and hire and lead the Bay Area robotics team as it grows.

What We're Looking For

• Six or more years of hands-on robot learning experience, including work in industry and a university research lab, plus a master's or doctoral degree in robotics, machine learning, or a related field.

• Experience training and evaluating robot policies in Isaac Sim, Isaac Lab, MuJoCo, or equivalent simulation environments.

• Practical experience with policy learning methods such as VLA fine-tuning, OpenVLA, π0, GR00T, imitation learning, diffusion policy, ACT, behavior cloning, or reinforcement learning in simulation.

• Experience with manipulation or grasping policies, and the ability to run controlled comparisons that vary training data while keeping seeds, checkpoints, and evaluation suites consistent.

• Ability to use evaluation results to drive changes to training data or simulation. Relevant tools include Python, PyTorch, NVIDIA Isaac, and USD.

Compensation & Benefits

Compensation is $260,000 to $300,000 USD annually. Visa sponsorship is not available.

Location

Hybrid role based in San Francisco, California, United States.