Senior Event-Based Robotics Research Engineer — VIO & Motion Estimation

Promethion UG

Berlin

Hybrid

EUR 65,000 - 90,000

Full time

9 days ago

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Job summary

Promethion Industries seeks a skilled researcher/engineer to advance VIO and state estimation for autonomous aerial robotics. You will drive event-based methods, asynchronous sensing, and IMU fusion, port algorithms to embedded hardware, and contribute to a state-estimation stack used in high-speed domains.

You will work with academic literature to produce reproducible, real-world implementations and collaborate with the core state-estimation team to validate and transition approaches into

Qualifications

  • Strong research or engineering background in VIO, visual odometry, SLAM or state estimation.
  • Experience with event cameras or asynchronous sensing.
  • Strong understanding of IMU fusion and nonlinear estimation.
  • Strong C++ skills.
  • Experience implementing research algorithms on real hardware.
  • Strong understanding of sensor timing, calibration and high-rate data processing.
  • Ability to work from academic literature to reproducible real-world implementation.

Responsibilities

  • Develop event-based VIO and motion-estimation approaches for high-speed aerial robotics.
  • Explore asynchronous optical flow, event-IMU fusion and direct velocity estimation.
  • Develop continuous-time estimation approaches suitable for high-rate asynchronous sensing.
  • Evaluate event-based methods for GNSS-denied and high-dynamic flight.
  • Build and validate hybrid frame + event + IMU estimators.
  • Investigate velocity-space estimation for terminal high-dynamic operation.
  • Characterize failure modes including scale drift, sensor mismatch and high angular rates.
  • Port promising research onto embedded compute and evaluate real latency and resource requirements.
  • Work directly with the core state-estimation team to transition validated approaches into the main stack.

Skills

VIO
Visual Odometry
SLAM
State Estimation
Event Cameras
Asynchronous Sensing
IMU Fusion
Nonlinear Estimation
C++ Skills
Hardware Prototyping

Job description

About Promethion Industries

Promethion Industries is a European defence technology company building autonomous supremacy systems for aerial and multi-domain operations. We design tightly integrated autonomy stacks in Europe to enable decisive autonomy for NATO-aligned forces, focusing on defensive and counter-system capabilities including anti-UAS and resilient autonomy under contested conditions.

Your mission with us
  • Develop event-based VIO and motion-estimation approaches for high-speed aerial robotics.

  • Explore asynchronous optical flow, event-IMU fusion and direct velocity estimation.

  • Develop continuous-time estimation approaches suitable for high-rate asynchronous sensing.

  • Evaluate event-based methods for GNSS-denied and high-dynamic flight.

  • Build and validate hybrid frame + event + IMU estimators.

  • Investigate velocity-space estimation for terminal high-dynamic operation.

  • Characterize failure modes including scale drift, low texture, sensor mismatch and high angular rates.

  • Port promising research onto embedded compute and evaluate real latency and resource requirements.

  • Work directly with the core state-estimation team to transition validated approaches into the main stack.

The offboarding work specifically highlights event+IMU fusion, direct velocity estimation and event-based high-speed state estimation, alongside concrete concerns around scale drift and embedded compute limits. Neuromorphic VIO and OF (1)

Your contribution to the team (required)
  • Strong research or engineering background in VIO, visual odometry, SLAM or state estimation.

  • Experience with event cameras or asynchronous sensing.

  • Strong understanding of IMU fusion and nonlinear estimation.

  • Strong C++ skills.

  • Experience implementing research algorithms on real hardware.

  • Strong understanding of sensor timing, calibration and high-rate data processing.

  • Ability to work from academic literature to reproducible real-world implementation.

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