Group Lead AI Engineering (human)

Neura Robotics
Europe +1 more
On-site

Who this role is best for

Best suited to experienced AI engineers with leadership potential working in robotics and AI product development in Europe.

Best fit for

  • Experienced AI engineers with leadership potential and a strong background in robotics AI systems
    — “7+ years of hands-on ML or robotics AI engineering, with at least 2 years in a formal or informal technical lead role.”
  • Individuals with deep expertise in at least two AI engineering domains like manipulation or MLOps
    — “Strong command of at least two of: vision-based perception, manipulation & control, reinforcement / imitation learning, multimodal foundation models, or scalable MLOps.”

Things to consider

  • Candidates must be fluent in English, with German language skills being a significant advantage.
    — “Professional English required; German is a strong plus (B2–C1).”

How to stand out

  • Highlight experience in transitioning AI research to production-ready systems.
    — “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.”
  • Showcase leadership in growing teams and mentoring individual contributors.
    — “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.”
  • Emphasize hands-on problem-solving with real robot hardware and simulation environments.
    — “Comfort working with real robot hardware and simulation environments (IsaacSim, MuJoCo, or equivalent).”
  • Demonstrate technical fluency in PyTorch, JAX, and cloud infrastructure in your project examples.
    — “Strong Python (C++ is a plus); practical PyTorch or JAX experience; familiarity with cloud infrastructure (AWS, GCP, or Azure)”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Own the technical roadmap of a sub-team
  • Lead and grow a high-performance team
  • Drive research-to-production transitions
Typical background
PhD in Computer Science, Robotics, Electrical Engineering, or related field

Skills & requirements

Required

AI EngineeringTechnical LeadershipResearch-to-production TransitionsCross-functional CollaborationEngineering QualityHands-on Problem-solving

Preferred

RoboticsElectrical Engineering

Stack & domain

AI EngineeringMLRoboticsVision-based PerceptionManipulation & ControlReinforcement / Imitation LearningMultimodal Foundation ModelsScalable MlopsLeadershipMentoringDecision-makingCommunicationTeamworkAI

About the role

Original posting from Neura Robotics via Ashby

YOUR MISSION & CHALLENGES

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

WHAT WE CAN LOOK FORWARD TO

  • 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).

Source: Neura Robotics careers (Ashby)

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