Robot Learning Engineer — Real-World RL & Teleoperation

Genesis; Greater London; On-site; GBP 60,000 - 100,000; Full time

Job summary

Genesis seeks a robotics engineer to develop and optimize a learning-based manipulation control stack, and to design a teleoperation system with smooth, precise motion and low latency. You will train robotic policies using reinforcement learning and imitation learning, deploy them, and diagnose latency in the control pipeline.

The role includes reducing the sim-to-real gap by co-optimizing simulation with real-world robot behavior, and collaborating with a driven team building general-purpose

Qualifications

• 5+ years of experience building and deploying real-world learning-based robotic systems.
• Passion for robotics engineering and demonstrated excellence.
• Exceptional ownership and initiative—solving problems independently.
• Methodical approach to complex tasks and strong attention to detail.

Responsibilities

• Develop and optimize a learning-based robotic manipulation control stack.
• Design and maintain a teleoperation system with low latency and precise motion.
• Train robotic policies using reinforcement learning and imitation learning.
• Deploy 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 behavior.
• Collaborate with a team focused on general-purpose Physical AI.

Skills

Python

C++

Robotics

Reinforcement learning

Job description

Genesis seeks a robotics engineer to develop and optimize a learning-based manipulation control stack, and to design a teleoperation system with smooth, precise motion and low latency. You will train robotic policies using reinforcement learning and imitation learning, deploy them, and diagnose latency in the control pipeline.

The role includes reducing the sim-to-real gap by co-optimizing simulation with real-world robot behavior, and collaborating with a driven team building general-purpose