Founding Research Scientist

-Greater London Founding Research Scientist What would you work on if you could help define the research agenda from day one?

We’re hiring a Founding Research Scientist to join an ambitious UK Physical AI startup building the models that will enable robots to understand, learn and act in the real world.

This is an opportunity to pursue difficult, open-ended research problems without being confined to an established roadmap. You’ll develop new ideas, test them on real robotic systems, and turn promising research into technology that works outside the lab.

What’s in it for you?

Founding role with significant equity

Help define the research agenda from the ground upWork at the frontier of robot learning, vision-language-action models and world models

Design and run experiments on real robotic hardware

Publish meaningful research while building technology with real-world impact

Work closely with a small, highly technical founding team

Have genuine ownership over which problems are worth solving and how to approach them

What you’ll work onLead research across robot learning, world models and VLA systems

Develop new approaches to model architectures, training and data collection

Design rigorous evaluation methods for Physical AI systems

Take ideas from first principles and papers through to prototypes and real-world robotic experiments

Investigate what enables models to generalise across tasks, environments and embodiments

Publish research and help establish the company’s long-term technical direction

What you’ll bring

Strong research experience across machine learning, robotics or computer vision

Deep understanding of modern deep learning methods

Excellent mathematical, experimental and problem-solving instincts

Hands-on experience training and evaluating ML models

The ability to form hypotheses, design experiments and learn quickly from results

Curiosity for problems where the answers — and sometimes even the right questions — aren’t obvious

Publications, benchmarks and open-source contributions are valuable signals, but they aren’t the deciding factor.

What matters most is the quality of your research thinking, the problems you choose to pursue, and your ability to turn ideas into experiments that teach us something new.