Machine Learning Engineer (f/m/d)

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 is a division of Hexagon – a global leader in precision measurement. The division develops humanoid robots for industrial sectors to address labor shortages and accelerate the transition from automation to autonomy. Our first humanoid, AEON, was launched in June 2025 and is already in pilots with five customers.

We are looking for a Machine Learning Engineer to develop and improve learning-based behaviors for our humanoid robots. You will work primarily on reinforcement learning (RL) and imitation learning (IL), training and iterating on policies, analyzing experiments, and addressing the gap between simulation and real-world robot performance.

Your Mission

Develop, train, and iterate on reinforcement learning policies for humanoid locomotion and manipulation

Analyze training metrics and experiment results from simulation and real robots, identify issues, and propose follow-up actions

Investigate sim-to-real gaps and develop approaches to improve the transfer of learned policies to real robots

Develop machine learning solutions in Python using frameworks such as PyTorch, TensorFlow, or JAX

Build and maintain RL/IL training pipelines, including environments, curricula, normalization, and evaluation

Evaluate learning algorithms and adapt them to the specific problem at hand, with support from experienced team members

Work collaboratively in a multicultural and interdisciplinary environment on a novel humanoid robot

Proactively identify opportunities for improvement and contribute ideas to the team

Your Skillset

What we are looking for

• PhD/MSc in Robotics, Computer Science, or a related technical field
• Python programming skills and experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX
• Ability to independently write and debug basic C++ code
• Hands-on experience developing and training reinforcement learning policies. Experience with imitation learning or related learning-based methods is a plus
• Ability to interpret training metrics and experimental results and use them to guide the next iteration
• Understanding of sim-to-real challenges in robotics and approaches to address them
• Autonomous and proactive working style, with a strong drive to experiment, learn, and solve problem

Nice to have

• Experience working with real robots
• Experience with modern RL/IL/ML approaches, such as transformers or cross-embodiment transfer learning
• Experience with Isaac Sim or other standard RL simulators
• Experience working independently with ROS2, including writing nodes and debugging interactions between them
• Experience defining objectives for your work and integrating them into a broader team plan or owning an epic

What You’ll Get

• Flexible working hours and a hybrid model for real work-life balance
• CHF 500 mobility credit for sustainable commuting
• Bonus system & strong pension contributions
• Tailored training & development opportunities
• Relocation support for a smooth start
• Discounts on health, mobility & entertainment
• Team events and a flat hierarchy where your voice counts
• A warm, international culture built on respect and collaboration

Hexagon Robotics is a division of Hexagon – a global leader in precision measurement. The division develops humanoid robots for industrial sectors to address labor shortages and accelerate the transition from automation to autonomy. Our first humanoid, AEON, was launched in June 2025 and is already in pilots with five customers.

We are looking for a Machine Learning Engineer to develop and improve learning-based behaviors for our humanoid robots. You will work primarily on reinforcement learning (RL) and imitation learning (IL), training and iterating on policies, analyzing experiments, and addressing the gap between simulation and real-world robot performance.

Your Mission

Develop, train, and iterate on reinforcement learning policies for humanoid locomotion and manipulation

Analyze training metrics and experiment results from simulation and real robots, identify issues, and propose follow-up actions

Investigate sim-to-real gaps and develop approaches to improve the transfer of learned policies to real robots

Develop machine learning solutions in Python using frameworks such as PyTorch, TensorFlow, or JAX

Build and maintain RL/IL training pipelines, including environments, curricula, normalization, and evaluation

Evaluate learning algorithms and adapt them to the specific problem at hand, with support from experienced team members

Work collaboratively in a multicultural and interdisciplinary environment on a novel humanoid robot

Proactively identify opportunities for improvement and contribute ideas to the team

Your Skillset

What we are looking for

• PhD/MSc in Robotics, Computer Science, or a related technical field
• Python programming skills and experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX
• Ability to independently write and debug basic C++ code
• Hands-on experience developing and training reinforcement learning policies. Experience with imitation learning or related learning-based methods is a plus
• Ability to interpret training metrics and experimental results and use them to guide the next iteration
• Understanding of sim-to-real challenges in robotics and approaches to address them
• Autonomous and proactive working style, with a strong drive to experiment, learn, and solve problem

Nice to have

• Experience working with real robots
• Experience with modern RL/IL/ML approaches, such as transformers or cross-embodiment transfer learning
• Experience with Isaac Sim or other standard RL simulators
• Experience working independently with ROS2, including writing nodes and debugging interactions between them
• Experience defining objectives for your work and integrating them into a broader team plan or owning an epic

What You’ll Get

• Flexible working hours and a hybrid model for real work-life balance
• CHF 500 mobility credit for sustainable commuting
• Bonus system & strong pension contributions
• Tailored training & development opportunities
• Relocation support for a smooth start
• Discounts on health, mobility & entertainment
• Team events and a flat hierarchy where your voice counts
• A warm, international culture built on respect and collaboration

Contact

Great robots need great people.

Contact

Silvia Dadin