Machine learning & robotics scientist

Our mission is to create advanced robots that can operate in complex environments, reducing human risk in conflict zones and enhancing efficiency in labor-intensive industries.

We are on the lookout for extraordinary engineers and scientists to join our team.

Your previous experience in robotics isn't a prerequisite — it's your talent and determination that truly count.

We expect that many of our team members will bring diverse perspectives from various industries and fields. We are looking for individuals with a proven record of exceptional ability and a history of creating things that work.

We like to be frank and honest about who we are, so that people can decide for themselves if this is a culture they resonate with. Please read more about our culture here (Sie können sich bewerben oder uns per E-Mail kontaktieren in dem Sie die untenstehende Online-Bewerbungsbox verwenden) .

• You like working in person with a team in Munich.
• You deeply believe that this is the most important mission for humanity and needs to happen yesterday.
• You are highly technical – regardless of the role you are in. We are building technology; you need to understand technology well.
• You care about aesthetics and design inside out. If it's not the best product ever, it bothers you, and you need to “fix” it.
• You don't need someone to motivate you; you get things done.

• Design, develop, and optimize reinforcement learning algorithms with world models for real-time control and locomotion of humanoid robots.
• Integrate learned policies into real-world robot platforms with hardware-in-the-loop validation.
• Collaborate with mechanical, perception, and embedded systems teams to ensure tight integration between hardware and software.
• Analyze and optimize control performance with a focus on robustness, energy efficiency, and adaptability.
• Contribute to the continuous development of our in-house training pipelines and tooling.

• Proficiency in Python and C++ for algorithm development and deployment.
• 2+ years of experience in machine learning (NNs, LVMs, VLAs) and reinforcement learning applied to robotics or similar real-time environments.
• Hands-on experience with physics simulation environments (e.g., Mu Jo Co , Isaac Lab).
• Experience with deep learning frameworks (e.g., PyTorch, JAX, Tensor Flow).
• Strong understanding of classical and modern control theory, locomotion dynamics, etc.
• Experience working with physical robots.
• Contributions to open-source ML or robotics projects.
• M.Sc. or Ph.D. in Robotics, Computer Science, Mechanical Engineering, or a related field.