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Posted 17 days ago

Open

Robot Learning

LondonHybridFull-time

AI Summary

Develop and optimize a learning-based robotic manipulation control stack, design a low-latency teleoperation system, and train robotic policies for manipulation and locomotion using reinforcement and imitation learning.

About this role

What You’ll Do

  • Develop and optimize a learning-based robotic manipulation control stack

  • Design and maintain a teleoperation system with smooth, precise motion and low latency

  • Train robotic policies for manipulation and locomotion with reinforcement learning and imitation learning

  • Deploy robotic policies and diagnose latency or bottlenecks in the control pipeline

  • Analyze and minimize the sim-to-real gap by co-optimizing simulation and real-world robot behavior

  • Collaborate with a team of driven individuals committed to building general-purpose Physical AI

What You’ll Bring

  • Passion for your craft and demonstrated excellence in robotics engineering

  • Exceptional ownership and initiative—finding and solving problems independently

  • Focus, attention to detail, patience, and a methodical approach to complex tasks

  • Production-level expertise in modern Python or C++

  • Extensive experience building and deploying real-world learning-based robotic systems (5+ years)

  • Bonus: Hands-on experience troubleshooting and maintaining robotic systems across mechanical, electrical, and software components

Skills

C++Control Pipeline DeploymentImitation LearningLatency OptimizationLocomotion PoliciesPythonReinforcement LearningRobotic ManipulationSim-to-real TransferTeleoperation Systems

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