About the Role

Join an early research team at a European AI company building data and evaluation methods for robot learning. You will investigate what improves robot performance, train and evaluate policies, and help turn research findings into datasets, benchmarks, and products.

What You'll Do

Train and fine-tune robot policies on datasets, then measure their impact.

Design benchmarks that assess policy performance on real-world tasks.

Select and run suitable training methods across research projects, from setup through evaluation.

Help set research priorities, including tasks, robot embodiments, and data quality standards.

Publish research through papers, open releases, and technical articles.

Coordinate research findings with clients, robotics partners, and data and marketing teams.

What We're Looking For

Hands-on research experience in physical AI or robot learning, such as imitation learning, robot reinforcement learning, vision-language-action models, or dexterous manipulation.

A completed or nearly completed PhD in robotics or machine learning, or an equivalent research record demonstrated through publications or research work.

Experience personally training and evaluating robot policies in simulation or on real hardware.

Evidence of research through publications at leading robotics or machine learning venues, work with robot hardware, or experience with large robotics datasets and pipelines.

Familiarity with relevant tools and data ecosystems, such as LeRobot, RLDS, or Open X-Embodiment.

Early-career researcher profile, from a PhD candidate near completion to a few years post-PhD.

Compensation & Benefits

Competitive salary plus equity. Relocation support is available. Visa sponsorship details were not provided.

Location

Full-time, on-site in Barcelona, Catalonia, Spain. Candidates must be based in Barcelona or willing to relocate.