Senior RL Robotics Controls Engineer - Remote/Hybrid

Elysium Robotics; Greater London; Hybrid; GBP 70,000 - 90,000; Full time

Benefits offered by this job

Work from home flexibility

Support of US leadership

Opportunity to solve complex problems

Collaborate with elite talent

Job summary

Elysium Robotics is seeking a Senior Robotic Controls & Reinforcement Learning Simulation Engineer to join their innovative team in the UK. This role focuses on developing and optimizing control algorithms for advanced robotic systems using proprietary elastic actuators.

Your responsibilities will include training robust control policies, managing simulation infrastructures, and driving the performance of our bio-inspired robotic systems. Join us to tackle challenging deep-tech problems while enjoying a flexible hybrid work environment.

Qualifications

• Strong background in Reinforcement Learning and ML-based robotic control.
• Deep expertise in Variable Stiffness / Impedance Control.
• Experience with tendon driven robotic systems.

Responsibilities

• Develop robust control policies using Reinforcement Learning.
• Design control strategies for elastic muscle systems.
• Manage computational data infrastructure for simulations.
• Develop control for dexterous manipulation and rhythmic tasks.
• Develop scalable control strategies utilizing elastic actuators.
• Minimize sim-to-real gaps through constant assessment.

Skills

Reinforcement Learning

Variable Stiffness Control

System Identification

Tendon Driven Systems

Algorithm Complexity

Job description

Elysium Robotics is seeking a Senior Robotic Controls & Reinforcement Learning Simulation Engineer to join their innovative team in the UK. This role focuses on developing and optimizing control algorithms for advanced robotic systems using proprietary elastic actuators.

Your responsibilities will include training robust control policies, managing simulation infrastructures, and driving the performance of our bio-inspired robotic systems. Join us to tackle challenging deep-tech problems while enjoying a flexible hybrid work environment.