About this role
Summary: Develop and improve learning-based behaviors for humanoid robots using reinforcement learning and imitation learning. The role involves training policies, analyzing simulation and real-world experiments, and bridging the gap between simulated and real robot performance.
Machine Learning Engineer (f/md)
#### 100% Zürich
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
- Decent C++ programming skills
- 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
- Generous vacation: 25–30 days depending on age
- 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
Great robots need great people.
Contact
Silvia Dadin
Senior Recruiter / HR Generalist
E-Mail: silvia.dadin@hexagon.com
Hexagon Robotics
Räffelstrasse 26, 8045 Zürich
https://robotics.hexagon.com/