Senior Reinforcement Learning Engineer

📋 Description

• Lead design, training, and deployment of RL policies for robot motion.
• Mentor engineers and establish best practices for policy workflows.
• Own RL training infrastructure and the sim-to-real pipeline.
• Shape internal ML tooling and experiment management (dashboards, pipelines).
• Collaborate with cross-functional teams to expand autonomous operations.
• Triage locomotion issues and improve policy robustness from field data.

🎯 Requirements

• PhD in robotics/ML/CS with RL focus or equivalent RL track record in robotics.
• Master's from ETH Zurich or EPFL with 5+ years of experience.
• Proven track record shipping ML models to the field and maintaining them.
• Solid grounding in robot control: motion control, state estimation, path planning, actuation.
• Experience using Gazebo or Isaac Sim; sim-to-real transfer, domain randomisation, reward shaping.
• Proficiency in Python and PyTorch; working knowledge of C++.

🎁 Benefits

• Competitive salary and employee stock ownership plan.
• Hybrid work in Zurich, Switzerland.
• Opportunities to work on cutting-edge robotics.