Team Lead AI Engineering – RoboGym

Location: Munich, Germany; on-site

Company

hirify.global develops physical AI systems and robotic capabilities through real-world training in industrial environments.

What you will do

• Lead, hire, and coach a team of AI Engineers developing deployable robotic skills.
• Manage the technical relationship with NEURA Gym partners, evaluating use cases, feasibility, algorithms, and data collection strategies.
• Oversee the end-to-end pipeline from teleoperation and data collection through training, simulation, deployment, and validation.
• Support on-site Robotics Engineers during live experiments and data collection while maintaining safety standards.
• Investigate data quality and model issues, review training pipelines, and resolve complex technical challenges.
• Connect NEURA Gym, Cloud, and Core AI teams and use deployment insights to improve products and capabilities.

Requirements

• Degree in Computer Science, Robotics, Electrical Engineering, or a related field, or equivalent practical experience.
• Hands-on experience developing machine learning solutions for robotics in at least two areas: vision-based manipulation, reinforcement or imitation learning, and Vision-Language-Action or multimodal foundation models.
• Experience leading engineers, projects, or technical initiatives.
• Practical experience with PyTorch or TensorFlow and strong Python programming skills.
• Experience with physical robotic systems and relevant robotics software stacks or middleware.
• Professional working proficiency in English is required; the role is on-site in Munich.

Nice to have

• C++ experience.
• Familiarity with AWS, Azure, or GCP.
• Experience with Isaac Sim, MuJoCo, or other robotic simulation environments.
• German language skills.
• Track record of delivering robotics or AI projects from concept to deployment with measurable impact.

Culture & Benefits

• Work directly with customers and domain experts to capture real-world knowledge.
• Collaborate with Robotics Engineering, Cloud, and Core AI teams.
• See AI systems deployed on physical robots rather than remaining as research prototypes.
• Contribute to product roadmap improvements based on live deployments and measurable performance metrics.