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Computer Vision Engineer - Localization

in 80331, München, Bayern, Deutschland
Unternehmen: SE3 Labs
Vollzeit position
Verfasst am 2026-09-23
Berufliche Spezialisierung:
  • Software Entwicklung
    Künstliche Intelligenz Ingenieur, Software-Ingenieur, Robotik, Python
Gehalts-/Lohnspanne oder Branchenbenchmark: 90000 - 130000 EUR pro Jahr EUR 90000.00 130000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Staff Computer Vision Engineer - Localization

Join SE3 Labs as Staff Computer Vision Engineer - Localization

Solve the hardest estimation and systems problems in our visual localization stack, from core algorithms to deployed software.

About SE3

SE3 Labs builds spatial intelligence and autonomy software for unmanned systems. We combine 3D computer vision, state estimation and AI to help autonomous platforms perceive their surroundings, know where they are and operate when GPS and other sensors become unreliable. Defence is a core application of our work today.

We are growing to a team of 100+ people. Join at a stage where you can shape our localization technology, help build the team and grow your responsibilities as the company expands.

Our founding team’s research has received more than 90,000 citations. You will work closely with technical founders and engineers with deep experience in computer vision and autonomous systems, turning that research depth into systems that work in the field.

About the Role

As a Staff Engineer, you will shape algorithm and architecture decisions, implement critical parts of the system, and help other engineers solve problems across sensors, estimation and onboard compute.

This is a hands-on individual contributor role. You will take ideas from research and recorded data through production code, live sensor testing and flight, working closely with the Team Lead and our robotics software, embedded, hardware and field teams.

What You’ll Work On
  • VIO, SLAM and Sensor Fusion: Build and improve localization algorithms for autonomous systems operating with degraded or unavailable GNSS. Our initial focus is UAVs, with methods that can extend to other robotic platforms.

  • Robustness: Solve difficult failures caused by low light, rain, fog, motion blur, vibration and sensor degradation. Investigate better estimation, learned methods and data where each can improve measured performance.

  • Mapping and Relocalization: Develop mapping, loop closure, relocalization and map-based navigation. Make pose, velocity and uncertainty estimates useful to planning, control and the rest of the autonomy stack.

  • Calibration and Timing: Solve problems in camera and IMU calibration, sensor synchronization, rolling shutter, latency and frame drops. Work across algorithms and integration to find the root cause.

  • Real-Time Deployment: Design and optimize production software for Jetson-class platforms and other constrained CPUs and GPUs. Measure the tradeoffs between accuracy, robustness, latency, memory and power.

  • Evaluation: Build the evaluation and replay tools that let us reproduce failures, compare approaches and detect regressions. Validate improvements on recorded data and deployed systems.

  • Technical Leadership: Lead difficult technical projects, review designs and code, and teach other engineers what you learn. Help the team choose where deeper algorithm work will make the largest difference.

Your Profile
  • You have personally built and deployed VIO, SLAM, localization or sensor-fusion systems. You can explain the parts you implemented, the alternatives you considered, the failures you solved and the measured results.

  • You have solved problems that span algorithms, sensors and runtime constraints, and can show improvements in accuracy, robustness or compute cost.

  • You have strong foundations in 3D geometry, linear algebra, probability, estimation and optimization, with practical experience in methods such as EKFs, factor graphs, nonlinear least squares and bundle adjustment.

  • You write production C++ for Linux systems and use Python for analysis, evaluation and tooling. Rust experience is a plus.

  • You have worked with real cameras and IMUs, calibration and timing. You use logs, reproducible experiments and regression tests to establish why a change…

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