Robotics ML Engineer: RL/IL for Humanoid Robots

CS Caritas Socialis GmbH; Zürich; Hybrid; CHF 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Mobility credit CHF 500

Bonus & pension

Relocation support

Health discounts

Team events

Flat hierarchy

Zusammenfassung

Hexagon Robotics in Zürich, part of Hexagon, is building humanoid robots for industrial use. We are seeking a Machine Learning Engineer to develop and refine reinforcement learning and imitation learning policies for locomotion and manipulation in real robots and simulations.

You will work with Python and ML frameworks, analyze experiments, address sim-to-real gaps, and contribute to end-to-end training pipelines, with a collaborative, multicultural team in a hybrid work setup.

Qualifikationen

• Hands-on RL/IL development for humanoid robotics.
• Strong background in robotics or computer science.
• Experience with ML frameworks and Python.

Aufgaben

• Develop, train, and iterate RL policies for locomotion and manipulation.
• Analyze training metrics from simulation and real robots.
• Address sim-to-real gaps and propose improvements.
• Build and maintain RL/IL training pipelines in Python.
• Evaluate algorithms and adapt them for real-world use.
• Collaborate in a multicultural, interdisciplinary team.
• Identify opportunities for improvement and contribute ideas.

Kenntnisse

PhD/MSc in Robotics

Python & ML frameworks

C++ programming

RL/IL experience

Experiment analysis

Sim-to-real challenges

Autonomous working

Ausbildung

PhD/MSc in Robotics or CS

Tools

PyTorch

TensorFlow

JAX

ROS2

Isaac Sim

Jobbeschreibung

Hexagon Robotics in Zürich, part of Hexagon, is building humanoid robots for industrial use. We are seeking a Machine Learning Engineer to develop and refine reinforcement learning and imitation learning policies for locomotion and manipulation in real robots and simulations.

You will work with Python and ML frameworks, analyze experiments, address sim-to-real gaps, and contribute to end-to-end training pipelines, with a collaborative, multicultural team in a hybrid work setup.