Team Lead AI Engineering

Physical AI can't be trained on internet data alone. Robots need to learn skills in the real world — by seeing, hearing and feeling real tasks in real environments. in real environments. That's the idea behind NEURA Gym: a global network of physical training centers where robots learn industrial tasks/skills directly from the people who know these processes inside out

As Team Lead AI Engineering – NEURAGym, you'll lead the team responsible for turning that expertise into deployable robotic capabilities. Working closely with customers, you'll help capture domain knowledge, guide data collection and teleoperation, and oversee the process from training through to deployment.

You'll lead a team of AI Engineers and act as the technical point of contact for partners as they bring new robotic applications to life. Success in this role requires balancing hands-on technical leadership with execution, ensuring that teleoperation, data pipelines, model training, and deployment come together as a reliable and scalable system.

This role is well suited to someone who enjoys building real-world AI systems, working closely with customers, and seeing their work deployed on physical robots rather than remaining in research prototypes or demonstrations.

Your mission & challenges

• Grow the team that makes NEURA Gym possible. Hire, coach, and lead a team of AI Engineers responsible for transforming partner expertise into deployable robotic skills.

• Own the technical relationship with NEURA Gym partners. Evaluate new use cases, determine technical feasibility, select the right algorithms, and define effective data collection strategies.

• Ensure the training pipeline runs smoothly end-to-end. Oversee the entire process from teleoperation and training through simulation, deployment, and validation, ensuring seamless execution across every stage.

• Be there when it matters most. Partner closely with on-site Robotics Engineers during live data collection and experiments, ensuring target behaviors are captured successfully while maintaining high safety standards in real-world environments.

• Provide hands-on technical support. Step in when the team encounters complex challenges, whether that's reviewing training pipelines, investigating data quality issues, or helping reproduce and resolve model-related bugs.

• Connect teams across NEURA. Serve as the bridge between NEURA Gym, Cloud, and Core AI teams, ensuring knowledge gained from one partner engagement benefits the broader organization.

• Help shape the product roadmap. Translate learnings from real-world deployments into improvements for both the NEURA Gym platform and NEURA's core AI capabilities.

• Measure what matters. Define and own key metrics such as skill success rate, time-to-validated skill, and data efficiency, using them to drive continuous improvement and team performance.

What we can look forward to

• A degree in Computer Science, Robotics, Electrical Engineering, or a related field, or equivalent practical experience.

• Strong hands-on experience developing machine learning solutions for robotics, with expertise in at least two of the following areas:

  • Vision-based manipulation

  • Reinforcement and/or imitation learning

  • Vision-Language-Action (VLA) models, multimodal foundation models, or related embodied AI approaches

• Experience leading engineers, projects, or technical initiatives, either through people management or formal technical leadership responsibilities.

• Practical experience with machine learning frameworks such as PyTorch or TensorFlow, solid programming skills in Python. Experience with C++ is a plus.

• Confidence working with physical robotic systems and relevant robotics software stacks and middleware.

• Familiarity with cloud platforms (AWS, Azure, or GCP) and/or robotic simulation environments such as Isaac Sim or MuJoCo is advantageous.

• Track record of delivering complex robotics or AI projects from concept to deployment, with measurable business or technical impact.

• Strong communication skills and the ability to translate between researchers, engineers, and end-users / customers, and other stakeholders.

• Professional working proficiency in English; German language skills are beneficial.