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Artificial intelligence researcher

Posted: 29 June
Offer description

Location: South of England (Hybrid options available) Level: Senior Sponsorship: Available Salary: Up to £140,000 Work Type: Onsite with real robots Relocation Support I'm supporting a well-backed robotics company, founded by repeat entrepreneurs to build one of the most ambitious real-world embodied AI stacks in Europe. They’re applying language vision control in a tightly integrated system that’s already moving fast from prototypes to deployment. This isn’t theoretical robotics. These roles are about putting ideas to the test by integrating ML, motion planning, and reasoning into production systems that do useful work in the real world. TWO OPEN ROLES: Decision-Making Systems Engineer You'll help shape the brain of the robot, building intelligent bridges between planning, perception, and pretrained models: Skill sequencing Hybrid planning learned policies LLM prompting as part of control pipelines Real-time integration with onboard sensors and motion layers Imitation Learning / Manipulation Engineer You’ll own high-capacity behaviour models, trained on human demos and sim-to-real environments. From data ingestion to model design to deployment on hardware, you're the force teaching the robot how to act. Large-scale data pipelines Vision-language-action learning Multitask imitation learning Deployment of learned skills on robot arms Why You’d Want This Real hardware, not simulation purgatory Direct mentorship from deeply technical founders and an elite team with some of Europe’s sharpest minds in RL, controls, and behaviour learning Truly interdisciplinary, if you like hacking agents, models, and mechatronics, this is your playground Ideal Background You don’t need to have done it all, but a few of these should ring true: Trained and deployed learned control policies Built robotic planning stacks involving LLMs or graph planners Debugged complex systems with perception, control, and comms layers Published in ICRA, CoRL, RSS, NeurIPS, or similar, and then shipped it Interested in safe RL, planning with priors, or diffusion-based policy learning APPLY NOW to discuss the details and see if this is the right fit for you!

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