Group Lead AI Engineering (human)

YOUR MISSION \& CHALLENGES
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NEURA is scaling its AI department to execute on our product roadmap. As Group Lead AI Engineering, you own a focused sub\-team within the AI department. You set technical direction, make critical architectural decisions, and unblock your engineers, while remaining hands\-on enough to review work, challenge approaches, and demonstrate what great looks like.

• Own the technical roadmap of your sub\-team: define goals, break them into executable engineering tracks, and ensure alignment with the broader AI and product strategy.


• Lead and grow a high\-performance team of AI engineers: recruit top talent, conduct technical interviews, set performance expectations, and develop individual contributors into senior engineers.


• Drive research\-to\-production transitions: evaluate state\-of\-the\-art methods, assess feasibility, and build the engineering bridges that get AI models running reliably on real robot hardware.


• Collaborate cross\-functionally with Software, Hardware and Product Management to align AI capabilities with platform requirements and customer use cases.


• Define and track engineering quality: establish testing standards, model evaluation pipelines, deployment metrics, and data governance practices for your domain.


• Step in hands\-on when your team hits hard blockers: review training runs, debug model behavior, challenge architectural assumptions, and lead by example in solving hard problems.


• Aggregate lessons learned and feed them back into the core AI roadmap

• An excellent Master's or PhD in Computer Science, Robotics, Electrical Engineering, or a related field


• 7\+ years of hands\-on ML or robotics AI engineering, with at least 2 years in a formal or informal technical lead role. Production systems experience is essential.


• Strong command of at least two of: vision\-based perception, manipulation \& control, reinforcement / imitation learning, multimodal foundation models, or scalable MLOps.


• Strong Python (C\+\+ is a plus); practical PyTorch or JAX experience; familiarity with cloud infrastructure (AWS, GCP, or Azure) and CI/CD for ML systems.


• Comfort working with real robot hardware and simulation environments (IsaacSim, MuJoCo, or equivalent). You understand that real\-world deployment is the only true test.


• Proven ability to set technical direction, mentor engineers, conduct code and design reviews, and make decisions under uncertainty.


• You translate between researchers, product managers, and hardware engineers without losing precision. Professional English required; German is a strong plus (B2–C1\).

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