Software Engineer, Robot Autonomy (Actuator Control & Locomotion), Intern

About the role

As a Reinforcement Learning Intern on Robot Autonomy, you will train locomotion and low-level control policies for legged security robots. You will work on the transition from simulation to real hardware, focusing on robot behavior across varied terrain and challenging weather conditions.

Responsibilities

• Train and evaluate reinforcement learning policies for locomotion and low-level control in simulation.
• Apply sim-to-real techniques such as domain randomization, reward design, and policy robustness methods.
• Test policy results on physical robots.
• Make policies robust to varied terrain, challenging weather, and noisy, delayed, or missing sensor data.
• Explore control approaches that transfer across robot embodiments with different actuators and dynamics.
• Build evaluation workflows with clear metrics and repeatable experiments in simulation and on hardware.
• Apply solid engineering practices including experiment tracking, version control, and reproducible training runs.

Required skills

• Reinforcement learning
• Robot dynamics
• Control theory
• Python
• PyTorch
• JAX
• Docker
• Git
• Isaac Sim
• MuJoCo
• Gazebo

Nice to have

• Physical robot deployment
• Legged robotics
• Actuator control
• Motor control
• Joint control
• C++
• ROS 2

Qualifications

• Currently pursuing a PhD in Robotics, Machine Learning, Computer Science, or a related field
• Recently completed a Master's degree in Robotics, Machine Learning, Computer Science, or a related field

Benefits

• Equity package

About the Company

Laelaps AI is a startup building intelligent software for physical security, enabling robots and sensors to handle dangerous and critical tasks. The company is based in Zurich and backed by visionary investors and advisors.