Senior Perception Engineer - VIO / SLAM / Sensor Fusion

SE3 Labs
München, Germany
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English, German
Experience level
Senior

Job location

München, Germany

Tech stack

Artificial Intelligence
Artificial Neural Networks
Computer Vision
C++
Nvidia CUDA
Information Engineering
Software Debugging
Linux
Microprocessors
Global Positioning Systems (GPS)
Inertial Navigation Systems
Python
Log Analysis
Regression Testing
Robotic Automation Software
Sensor Fusion
Rust
Graphics Processing Unit (GPU)
Real Time Systems
Virtual Reality
Deep Learning
Information Technology
Low Latency
Production Code
GNSS

Job description

As Senior Perception Engineer - VIO / SLAM / Sensor Fusion, you will own core parts of the real-time perception and localization stack for our autonomous systems. You will develop and deploy the algorithms that let our platforms estimate motion, maintain pose, build spatial understanding, and operate reliably in degraded or GPS-denied environments.

You will work across visual-inertial odometry, SLAM, sensor fusion, calibration, time synchronization, mapping, and real-time systems. Your work will sit at the center of our autonomy platform: connecting cameras, IMUs, GNSS, onboard compute, control systems, payloads, and Spatial AI models into a coherent understanding of the world.

This is a hands-on engineering role. You will design algorithms, write production code, analyze logs, debug sensor issues, validate performance in simulation and flight, and work closely with robotics software, embedded, hardware, and field teams to turn perception research into fieldable capability., * Continuously push the boundary of what's possible: Improve state estimation capabilities in very difficult field conditions during heavy rain, snow, fog, in the night, under strong vibration, motion blur, imperfect calibration and sensor degradation. Utilize improved fusion, novel deep learning methods and our data engine.

  • VIO & State Estimation: Build, tune, and deploy robust visual-inertial odometry and state-estimation pipelines for robotics systems operating in dynamic, outdoor, and GPS-challenged environments. Initial focus is on UAVs, but we want to build algorithms that work well for any robotics system.
  • Sensor Fusion: Fuse and synchronize data from cameras, IMUs, magnetometers, barometers, and other onboard sensors into reliable pose, orientation, uncertainty estimates, and spatial context for downstream autonomy.
  • SLAM & Re-localization: Build mapping, loop closure, re-localization, and map-based navigation capabilities that let our systems maintain spatial understanding across missions, environments, and degraded sensor conditions.
  • Calibration & Timing: Own intrinsic, extrinsic, and temporal calibration workflows. Diagnose drift, latency, frame drops, sync issues, rolling-shutter effects, vibration, and sensor degradation.
  • Real-Time Deployment: Optimize perception pipelines for onboard compute, including Nvidia Jetson-class platforms, low-power edge CPUs/GPUs, and resource-constrained robotic systems.
  • Validation & Regression: Build replayable log pipelines, evaluation datasets, test metrics, and automated regression tests to measure localization accuracy, robustness, latency, and failure modes on a huge company-internal benchmark.
  • Field Debugging: Analyze real mission logs, reproduce failures, isolate root causes, and improve the system until it works not only in ideal conditions, but in the field.
  • Autonomy Integration: Define clean interfaces to planning, control, fleet coordination, operator UI, and Spatial AI systems so that perception outputs are usable, reliable, and explainable.
  • Technical Leadership: Mentor engineers, review architecture and code, raise engineering standards, and help define the long-term perception roadmap for SE3's autonomous systems., * Coding / Algorithm Interview: (90 min): We work through a practical perception, estimation, or robotics software problem together

Requirements

Do you have experience in Rust (programming language)?, Do you have a Master's degree?, * Most importantly, you're structured, fast-moving, and mission-driven. You don't wait for perfection. You iterate fast. You love building things that last and analyse and fix root cause problems over applying patches.

  • You hold an M.Sc., Ph.D., or equivalent practical background in Robotics, Computer Vision, Electrical Engineering, Computer Science, Aerospace Engineering, or a related technical field.
  • You bring several years of hands-on experience building perception, SLAM, VIO, localization, sensor-fusion, or state-estimation systems for real-world robotics, AR/VR, autonomous vehicles, drones, or adjacent domains.
  • You have strong foundations in 3D geometry, linear algebra, probability, estimation theory, optimization, filtering, and real-time robotics systems.
  • You are strong in C++, Python or Rust and comfortable writing production-quality software for Linux-based robotic systems.
  • You have practical experience with techniques such as EKF, factor graphs, nonlinear least squares, bundle adjustment, visual odometry, inertial navigation, calibration, and multi-sensor fusion.
  • You have worked with real sensors and understand that perception failures often come from timing, calibration, vibration, lighting, motion blur, data quality, or integration issues rather than from the algorithm alone.
  • You care about metrics, logs, reproducibility, and systematic validation. You don't just make a demo work once; you build the tools to know when it works, when it fails, and why.
  • 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., * Technical Interview (1 hr): We dive into your experience with perception, state estimation, SLAM/VIO, robotics, and real-world debugging

Benefits & conditions

  • Real Ownership: Get equity early, real stock options to participate directly in SE3's growth
  • Work Environment to Excel at: Find a high-quality and modern toolset, flat hierarchy and a skilled, driven team which will push the limits together with you
  • AI-boosted workplace: We empower every employee with best-in-class AI tools and agents, giving you unlimited access to the latest advancements and a true productivity edge
  • 31 Paid Days Off: 30 vacation days plus your birthday off
  • Well-being Access: Free membership to gyms, yoga, and wellness through EGYM Wellpass
  • Team Offsites: We go on 2 company retreats per year, our last ones were in Italy and Greece
  • Mentorship: Work closely with experienced engineers and get paired with a professional mentor to support your growth

About the company

SE3 Labs is building Spatial AI by combining 3D computer vision with large language models. We believe the ability to reason about and act within physical space is foundational to unlocking the next generation of automation, from construction to smart infrastructure, and ultimately, defence. Now, we're bringing Spatial AI into the sky through high-performance UAVs that can perceive, localize, coordinate, and act in the real world. This requires perception systems that are not just accurate in a notebook, but robust on real sensors, on real compute, in real missions.

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