Team Lead AI Engineering – Neura Gym

Location: Aachen, Germany

Company

hirify.global develops physical AI systems and the NEURA Gym network, where robots learn industrial skills in real-world training centers.

What you will do

• Hire, coach, and lead AI Engineers building deployable robotic skills.
• Lead 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 data collection and experiments while maintaining high safety standards.
• Investigate training pipeline, data quality, and model-related issues, providing hands-on technical support.
• Connect NEURA Gym, Cloud, and Core AI teams and translate deployment learnings into product and AI roadmap improvements.

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, including at least two of: vision-based manipulation, reinforcement or imitation learning, and Vision-Language-Action or multimodal foundation models.
• Experience leading engineers, projects, or technical initiatives.
• Strong Python programming skills and practical experience with PyTorch or TensorFlow.
• Confidence working with physical robotic systems, robotics software stacks, and middleware.
• Professional working proficiency in English is required.

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 complex robotics or AI projects from concept to deployment with measurable impact.

Culture & Benefits

• Work on physical AI systems deployed on real robots rather than research prototypes alone.
• Collaborate directly with customers and end-users to capture domain expertise and develop robotic applications.
• Define operational metrics including skill success rate, time-to-validated skill, and data efficiency.
• Work across AI engineering, robotics, cloud, and core AI teams.