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Open nowPosted 6 hours ago

Group Lead AI Engineering (Mensch)

Neura Robotics421 open roles

Where
Europe
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Your applicationOpen nowGroup Lead AI Engineering (Mensch)Neura Robotics · Europe
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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. Neura Robotics postings stay open a median of 32 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 6 hours ago

Neura Robotics median: 32 days open

The posting

DEINE MISSION & HERAUSFORDERUNGEN

NEURA skaliert seine AI-Abteilung, um unsere Produkt-Roadmap umzusetzen. Als Group Lead AI Engineering verantwortest du ein fokussiertes Sub-Team innerhalb der AI-Organisation. Du gibst die technische Richtung vor, triffst entscheidende Architekturentscheidungen und unterstützt dein Team dabei, Herausforderungen zu überwinden — gleichzeitig bleibst du nah genug an der Technik, um Arbeit zu reviewen, Ansätze kritisch zu hinterfragen und selbst vorzuleben, wie exzellentes Engineering aussieht.

DEINE AUFGABEN

- Verantworte die technische Roadmap deines Teams: definiere Ziele, übersetze sie in umsetzbare Engineering-Streams und stelle die Abstimmung mit der übergeordneten AI- und Produktstrategie sicher.

- Führe und entwickle ein leistungsstarkes Team von AI Engineers: gewinne Top-Talente, führe technische Interviews, setze klare Erwartungen und entwickle Mitarbeitende zu Senior Engineers weiter.

- Treibe den Transfer von Research zu Production voran: evaluiere State-of-the-Art-Methoden, prüfe Machbarkeit und baue die technischen Brücken, die AI-Modelle zuverlässig auf realer Robotik-Hardware zum Laufen bringen.

- Arbeite cross-funktional mit Software-, Hardware- und Product-Teams zusammen, um AI-Fähigkeiten mit Plattformanforderungen und Customer Use Cases abzustimmen.

- Definiere und überwache Engineering-Qualitätsstandards: Testing-Standards, Model-Evaluation-Pipelines, Deployment-Metriken und Data-Governance-Praktiken innerhalb deines Verantwortungsbereichs.

- Werde hands-on aktiv, wenn dein Team auf komplexe Blocker stößt: reviewe Trainingsläufe, debugge Modellverhalten, hinterfrage Architekturentscheidungen und führe durch technisches Vorbild.

- Sammle Learnings aus Projekten und speise diese aktiv in die Core AI Roadmap zurück.

WAS DU MITBRINGST

- Einen hervorragenden Master- oder PhD-Abschluss in Informatik, Robotik, Elektrotechnik oder einem verwandten Fachgebiet.

- 7+ Jahre praktische Erfahrung in ML- oder Robotics-AI-Engineering, davon mindestens 2 Jahre in einer formellen oder informellen technischen Lead-Rolle. Erfahrung mit produktiven Systemen ist essenziell.

- Fundierte Expertise in mindestens zwei der folgenden Bereiche:

- Vision-based Perception

- Manipulation & Control

- Reinforcement / Imitation Learning

- Multimodale Foundation Models

- Skalierbare MLOps-Systeme

- Sehr gute Python-Kenntnisse (C++ ist ein Plus), praktische Erfahrung mit PyTorch oder JAX sowie Kenntnisse in Cloud-Infrastruktur (AWS, GCP oder Azure) und CI/CD für ML-Systeme.

- Freude an der Arbeit mit realer Robotik-Hardware und Simulationsumgebungen wie IsaacSim, MuJoCo oder vergleichbaren Tools. Du weißt: Der echte Test findet immer in der realen Welt statt.

- Nachweisbare Fähigkeit, technische Richtung vorzugeben, Engineers zu coachen, Code- und Design-Reviews durchzuführen und Entscheidungen unter Unsicherheit zu treffen.

- Du kommunizierst souverän zwischen Research, Product Management und Hardware Engineering, ohne technische Präzision zu verlieren.

- Verhandlungssicheres Englisch; Deutschkenntnisse (B2–C1) sind ein starkes Plus.

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