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# Staff Computer Vision Engineer - Localization

- **Company:** SE3 Labs
- **Location:** München, Germany
- **Contract:** Permanent contract
- **Skills:** Artificial Neural Networks, Computer Vision, C++ (Programming Language), Nvidia CUDA, Software Debugging, Linux, Microprocessors, Python (Programming Language), Regression Testing, Sensor Fusion, Graphics Processing Unit (GPU), Production Code, GNSS
- **Published:** September 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fbfd727b7c4cabb9

## About the Role

* 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 works.
 * You have led substantial technical work and helped other engineers improve their designs and implementation. You remain comfortable writing and debugging the critical code yourself.
 * You have a master's degree, PhD or equivalent practical experience in a relevant technical field.
 * You speak fluent English; German is a plus. Given the nature of SE3's work in the defence sector, candidates must be eligible to work on defence-related projects and, where required, obtain the relevant security clearance., * Experience deploying perception systems on Nvidia Jetson, embedded CPUs/GPUs, writing CUDA kernels, optimizing deep neural networks for edge deployment.
 * Experience with LWIR thermal cameras (for navigation), rolling shutter effects, visual-inertial calibration, multi-camera rigs, fisheye/wide-angle lenses or monocular depth.
 * Experience with GNSS-denied navigation in UAV context, terrain-relative navigation, map-based localization and re-localization.
 * Experience building evaluation datasets, replay systems, perception observability, log tooling, and automated regression pipelines.
 * Publications or open-source contributions in SLAM, VIO, 3D computer vision, state estimation, or robotics are welcome, but not required., * Coding / Algorithm Interview: (90 min): We work through a practical perception, estimation, or robotics software problem together
 * Technical Interview (1 hr): We dive into your experience with perception, state estimation, SLAM/VIO, robotics, and real-world debugging
 * Team Dinner / Lunch: Meet the team and see whether it is a strong fit on both sides.

## Description

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.