Research Scientist - Embodied World Models

UMA; Paris; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

UMA is pioneering physical AI for humanoid robots. As a Research Scientist on the World Models team, you will own end-to-end research to enable planning, reasoning, and prediction of action outcomes in real robots.

You will collaborate with teams that built robots at Tesla Optimus, DeepMind, Google Brain, and HuggingFace. You’ll work on world-models, self-supervised pretraining, and integrating research with the control stack to ship real products in industrial settings.

Qualifications

• PhD (or equivalent industry research track) in robotics or related fields with papers or shipped systems.
• Experience with large-scale training, efficient inference and fast experimentation.
• End-to-end ownership mindset and ability to ship real products.

Responsabilités

• Design, run, and analyze experiments on world models, planning, and reasoning in simulation and real-world benchmarks.
• Own the stack from data processing, model training to evaluation on real robots.
• Advance self-supervised pretraining across video and action data for real-world manipulation and locomotion.
• Integrate with hardware, work with control stack, debug closed-loop behavior, and iterate in real-world conditions.
• Document and present findings, mentoring engineers turning research into products.

Connaissances

World models

Planning

Self-supervised learning

Reinforcement learning

Video modeling

Formation

PhD in robotics or related field

Description du poste

Your Mission

At UMA, we’re pushing the frontier of physical AI by teaching robots to understand, plan, and reason in the physical world. A critical part of this effort is building world models that can predict the outcomes of actions before they are executed on a robot.

At UMA, we’re pushing the frontier of physical AI by teaching robots to understand, plan, and reason in the physical world. A critical part of this effort is building world models that can predict the outcomes of actions before they are executed on a robot.

As a Research Scientist on the World Models team, you’ll own a piece of that frontier and drive it end to end: from ideas to real-world capabilities for humanoid robots deployed in the industry. You’ll have the autonomy of a research lab and the urgency of a startup shipping real products, working alongside people who built robots at Tesla Optimus, DeepMind, Google Brain and LeRobot at HuggingFace.

Key Responsibilities

• Design, run, and analyze original experiments on world models, planning, and reasoning, in simulation and real-world benchmarks.
• Own the stack from data processing, model training to evaluation on real robots.
• Push the frontier on self-supervised pretraining across video and action data for real-world manipulation and locomotion.
• Take your research all the way onto hardware, integrating with the control stack, debugging closed-loop behaviour, and iterating against the messiness of the real world.
• Document and present your work, and mentor the engineers who help bring it to life.

What You Bring To The Table

• A PhD (or equivalent industry research track) in robotics, representation learning, world models, self-supervised learning, RL/planning, or video modeling with a track record of papers and/or shipped systems.
• Real depth in the relevant stack: large-scale training, efficient inference, fast experimentation.
• The rare combination of research originality and engineering pragmatism with end to end ownership.
• Experience with latent world models like JEPA is highly valued; the ability to learn fast and bet well matters more than a specific paper on your CV.
• Bonus: You’ve worked in early-stage startups or the core teams of big companies building humanoids or highly-dexterous robots.
• UMA is an inclusive workplace that values exceptional builders over perfect pedigrees. Whatever your background, identity, or journey, if you don't meet every criterion but believe you can have an outsized impact here, we strongly encourage you to apply.