Robot Learning / Embodied AI
We’re partnering with a venture-backed robotics startup building systems that allow humans to extend their physical capabilities through intelligent robotic platforms.
The company recently secured new funding and is expanding its AI research team to develop learning systems for dexterous manipulation and real-world robotic autonomy.
This role sits at the intersection of robot learning, multimodal models, and real-world deployment.
The focus is not simulation research alone.
The work is about taking cutting-edge robot learning approaches and making them function reliably on physical systems.
Why this opportunity is interesting
Work on robot learning systems that bridge human teleoperation and autonomous behaviour.
Build learning pipelines for dexterous manipulation and mobile robotics.
Join a small team of roboticists and AI researchers working on real-world embodied intelligence systems.
Engineers joining now will have the opportunity to shape the core AI architecture before the organisation scales.
The kinds of problems you’ll work on:
Training imitation learning and reinforcement learning policies for robotic manipulation.
Developing diffusion-based and transformer-based control models for robots.
Building scalable systems for robot data collection, training and real-time inference.
Integrating perception, learning and control systems into production robotic platforms.
Working closely with robotics engineers to translate research into deployable systems.
This role will match best with researchers or engineers working in robot learning / embodied AI.
Experience with:
* Reinforcement learning or imitation learning for robotics
* Diffusion policies or transformer-based control models
* Frameworks such as ACT, PI0, GR00T, HIL-SERL or related robot learning stacks
* Deep learning with PyTorch or TensorFlow
* Robotics software stacks such as ROS, C++, Python
Experience with robot manipulation, navigation or perception is particularly valuable.
Team environment
This is a high ownership environment with a small technical team.
The engineers joining now will have the opportunity to influence both the research direction and the production systems that will power the next generation of robotic applications.