Onsite London: Robotics RL Engineer - Manipulation Policy

Secure Consult; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

Secure Consult in London is seeking a hands-on ML engineer to advance reinforcement learning for robotic manipulation. You will work across simulation and real-world environments, building robust policies and deployment pipelines.

The role requires 3+ years in deep learning for robotics, strong Python and PyTorch or JAX skills, and familiarity with robotics simulators like MuJoCo or Isaac Sim. Onsite, full-time position in London.

Qualifications

• 3+ years building deep learning systems with delivered models or publications.
• Experience applying reinforcement learning with deep neural networks in practical domains.
• Strong proficiency in Python and PyTorch or JAX.

Responsibilities

• Develop and train reinforcement learning models for robotic manipulation tasks in simulation and real-world settings.
• Collaborate across teams to create robust manipulation policies and integration pipelines.
• Design diverse manipulation tasks in simulation and contribute to deployment workflows.
• Collect trajectories with teleoperation teams for behavior cloning.
• Establish real-world RL training pipelines and bridge sim-to-real gaps.
• Document trade-offs and present clear results to stakeholders.

Skills

Deep learning

Reinforcement learning

Python

PyTorch

JAX

Robotics simulation

Tools

MuJoCo

Isaac Sim

Ray

Job description

Secure Consult in London is seeking a hands-on ML engineer to advance reinforcement learning for robotic manipulation. You will work across simulation and real-world environments, building robust policies and deployment pipelines.

The role requires 3+ years in deep learning for robotics, strong Python and PyTorch or JAX skills, and familiarity with robotics simulators like MuJoCo or Isaac Sim. Onsite, full-time position in London.