H

Machine Learning Engineer - Robotics

hexagon robotics Switzerland
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AI Summary

Develop and improve learning-based behaviors for humanoid robots using reinforcement learning and imitation learning. Train and iterate on policies, analyze experiments, and address sim-to-real gaps. Requires Python, machine learning frameworks, and hands-on RL/IL experience.

Key Highlights
Train and iterate on RL/IL policies for humanoid robots
Analyze training metrics and experiment results from simulation and real robots
Investigate sim-to-real gaps and improve policy transfer to real robots
Key Responsibilities
Train and iterate on reinforcement learning and imitation learning policies
Analyze training metrics and experiment results from simulation and real robots
Investigate sim-to-real gaps and develop approaches to improve 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 specific problems
Work collaboratively in a multicultural and interdisciplinary environment on a novel humanoid robot
Proactively identify opportunities for improvement and contribute ideas to the team
Technical Skills Required
Python Machine Learning Reinforcement Learning
Benefits & Perks
Flexible working hours and hybrid model
Generous vacation: 25–30 days depending on age
CHF 500 mobility credit for sustainable commuting
Bonus system and strong pension contributions
Tailored training and development opportunities
Relocation support for a smooth start
Discounts on health, mobility and entertainment
Team events and flat hierarchy
Warm, international culture built on respect and collaboration
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
Decent C++ programming skills
Experience defining objectives for your work and integrating them into a broader team plan or owning an epic

Job Description


Machine Learning Engineer (f/m/d)

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

  • Train and iterate on reinforcement learning and imitation learning policies, with a focus on reaching effective solutions efficiently
  • 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
  • Hands-on experience with reinforcement learning, imitation learning, or related machine learning methods
  • 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



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