Neura Robotics

Cognitive robots with perception, manipulation, collaboration

Group Lead Robotics Perception - Mapping & Navigation

Robotics & Autonomous SystemsConfirmed live in the last 24 hours

Full-timeRiederich, GermanyNo salary listed

About the Job

Requirements

A Master’s or PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
At least 7 years of experience in robotics perception, SLAM, or navigation, including at least 2 years of technical leadership and deployments on real robots in production or field use.
Deep knowledge of state estimation, sensor fusion, and SLAM, including methods such as factor graphs, visual-inertial odometry, and LiDAR SLAM.
A strong background in 3D computer vision and learning-based perception.
Solid experience with motion-planning and navigation stacks such as ROS 2, Nav2, and MoveIt.
Experience with simulation tools such as Isaac Sim, Gazebo, and MuJoCo, and sim-to-real transfer.
Strong knowledge of C++, Python, Linux, PyTorch, and libraries such as GTSAM, Ceres, Open3D, PCL, or OpenCV.
Strong leadership and communication skills.
Fluent spoken and written English.

Responsibilities

Own the technical roadmap for perception, mapping, and navigation, from research prototypes through production deployment on real robots.
Build and lead a team of perception, SLAM, and navigation engineers, fostering the team and supporting each individual’s development.
Advance multi-sensor perception using RGB-D, stereo, LiDAR, IMU, and wheel odometry, including calibration, time synchronization, and sensor fusion.
Lead development of SLAM, localization, and map management, including 2D/3D, semantic and long-term maps, multi-session mapping, and map updates in changing environments.
Own 3D scene understanding, including object detection, segmentation, pose estimation, and scene representations such as occupancy, voxel, mesh, and neural fields, to support manipulation and planning.
Advance global and local path planning, obstacle avoidance, navigation among dynamic and human obstacles, and whole-body motion in tight spaces.
Work with edge AI and hardware teams to meet real-time requirements on embedded hardware.
Work with the safety team to meet autonomous-motion requirements, including standards such as ISO 13482, ISO 3691-4, and ISO 10218.
Build datasets, ground truth, key performance indicators, and regression tests in simulation and on hardware.
Personally investigate difficult field issues such as localization failures, drift, degenerate environments, and edge cases.

Desired Qualifications

German proficiency at B2 to C1 level is a strong plus.

Deine Mission & Herausforderungen

Technische Roadmap: Du verantwortest die technische Roadmap für Perception, Mapping und Navigation, von Forschungsprototypen bis zum produktiven Einsatz auf echten Robotern.
Team aufbauen & führen: Du stellst ein Team aus Perception-, SLAM- und Navigation-Engineers auf, förderst es und begleitest die Entwicklung jedes Einzelnen.
Multi-Sensor-Perception: Du treibst die Wahrnehmung mit mehreren Sensoren voran (RGB-D, Stereo, LiDAR, IMU, Radodometrie), inklusive Kalibrierung, Zeitsynchronisation und Sensor Fusion.
SLAM, Lokalisierung & Kartenverwaltung: Du leitest die Entwicklung von SLAM, Lokalisierung und Map Management (2D/3D, semantische und Langzeitkarten, Multi-Session-Mapping, Kartenupdates in sich verändernden Umgebungen).
3D-Szenenverständnis: Du verantwortest Objekterkennung, Segmentierung, Posenschätzung und Szenenrepräsentationen (Occupancy, Voxel, Mesh, Neural Fields), die Manipulation und Planung speisen.
Navigation: Du treibst globale und lokale Pfadplanung, Hindernisvermeidung, die Navigation bei dynamischen und menschlichen Hindernissen sowie Ganzkörperbewegungen in engen Räumen voran.
Echtzeit-Performance: Du sorgst gemeinsam mit den Edge-AI- und Hardware-Teams dafür, dass die Echtzeitanforderungen auf eingebetteter Hardware erfüllt werden.
Funktionale Sicherheit: Du arbeitest mit dem Safety-Team zusammen, damit die Anforderungen an autonome Bewegung erfüllt werden (z. B. ISO 13482, ISO 3691-4, ISO 10218).
Simulation, Datenpipelines & Evaluation: Du baust Datensätze, Ground Truth, KPIs und Regressionstests in Simulation und auf Hardware auf.
Hands-on bei schwierigen Problemen: Du packst selbst an, wenn es um Lokalisierungsfehler, Drift, degenerierte Umgebungen oder Edge Cases im Feld geht.

Was du mitbringst

Abschluss: Master oder PhD in Robotik, Informatik, Elektrotechnik oder einem verwandten Fachgebiet.
Erfahrung: 7+ Jahre in Robotik-Perception, SLAM oder Navigation, davon 2+ Jahre technische Führung und Deployments auf echten Robotern im produktiven oder Feldeinsatz.
State Estimation & SLAM: Tiefes Wissen zu State Estimation, Sensor Fusion und SLAM (z. B. Factor Graphs, Visual-Inertial Odometry, LiDAR SLAM).
3D Computer Vision: Starker Hintergrund in 3D Computer Vision und lernbasierter Perception.
Motion Planning & Navigation: Solide Erfahrung mit Motion-Planning- und Navigation-Stacks (z. B. ROS 2, Nav2, MoveIt).
Simulation: Erfahrung mit Simulationstools (z. B. Isaac Sim, Gazebo, MuJoCo) und Sim-to-Real-Transfer.
Tech-Stack: Starke Kenntnisse in C++ und Python, Linux, PyTorch sowie Bibliotheken wie GTSAM, Ceres, Open3D, PCL oder OpenCV.
Führung & Kommunikation: Starke Führungs- und Kommunikationsfähigkeiten, sicheres Englisch in Wort und Schrift. Deutsch auf B2- bis C1-Niveau ist ein großes Plus.

About the Company

Neura Robotics

Cognitive robots with perception, manipulation, collaboration

Neura Robotics builds cognitive robots for industrial and service settings, combining perception, manipulation, and human collaboration. It develops both the hardware and the software stack for Physical AI, creating robot platforms like MAiRA, MAV, LARA and MiPA along with training infrastructure. The system works by integrating sensing, decision-making, and manipulation capabilities on a hardware-software stack that can be deployed in large-scale production, with the company planning robots fleets and NEURA Gyms for ongoing training and improvement. What sets Neura Robotics apart is its end-to-end approach to Physical AI, including a focus on mass production, an established global deployment plan, and a broad ecosystem of strategic backers and partners that support scaling and international expansion. The goal is to enable worldwide deployment of its robot platforms and associated training infrastructure, turning physical AI into widely available industrial and service automation.

Company size: 501-1,000
Company stage: Series C
Total funding: $1.7B
Headquarters: Metzingen, Germany
Founded: 2019

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