RL Applied Scientist: Learning-Based Navigation & Locomotion

Robotics and AI Institute; Zürich; On-site; CHF 120,000 - 180,000; Full time

Job summary

Robotics and AI Institute in Zürich invites a committed Applied Scientist to advance reinforcement learning for mobile robots. You will develop end-to-end control from sensor data and translate research into deployable systems.

The role requires hands-on ML and robotics experience, strong coding skills in Python or C++, and collaboration with hardware teams to validate algorithms on real hardware.

Qualifications

• MS/PhD or equivalent in robotics, CS, or related fields.
• 2+ years of research and development experience.
• Proficiency in Reinforcement Learning, Control, Robotics, or Imitation Learning.
• Experience with sim-to-real for legged robots or highly dynamic mobile vehicles.
• Experience in perception-based control.
• Advanced programming in Python or C++.
• Experience with PyTorch and robotic simulation.

Responsibilities

• Develop RL-based navigation or locomotion methods from sensor data.
• Work on end-to-end control for mobile robots in simulation and real hardware.
• Collaborate with hardware teams to validate models on legged robots.

Skills

Reinforcement Learning

Python or C++

Deep learning (PyTorch)

Robotics perception

Sim-to-real for legged robots

RL/Control/Imitation Learning

Education

MS/PhD in robotics or CS

Tools

ROS/ROS2

Docker

Robotic simulation

Job description

Robotics and AI Institute in Zürich invites a committed Applied Scientist to advance reinforcement learning for mobile robots. You will develop end-to-end control from sensor data and translate research into deployable systems.

The role requires hands-on ML and robotics experience, strong coding skills in Python or C++, and collaboration with hardware teams to validate algorithms on real hardware.