Robotics Engineer - Detection & Tracking (gn) @ Space Defence Venture, Munich

Responsibilities

• You will help build the autonomy architecture for a real-world robotic defence system.
• That means perception, tracking, state estimation, and control working together in real time on edge hardware. Your work will determine whether the system detects a target, understands what it is seeing, estimates its own motion correctly, and keeps the effector locked on.
• This is one of the first engineering roles. You will work directly with the three founders and have significant influence over core technical decisions from day one. You will not be handed a mature stack to maintain; you will help create the stack, test it in the real world, and push it toward operational use.
• The work will be broad and practical. You might be tuning a detector, debugging a camera pipeline, chasing latency through ROS2 nodes, fixing bad timestamps, compensating for ego-motion, calibrating sensors, or running field tests with hardware that fails in new ways every time.
• The expectation is not that you know everything. It is that you have seen enough real systems to know where they break, and that when they do, you can figure it out fast.
• You will own the robotics stack from perception through to actuation, including:
• Real-time object detection, classification, and multi-object tracking
• State estimation and sensor fusion across GPS, IMU, compass / magnetometer, and motor encoders
• Camera geometry, calibration, coordinate frames, and ego-motion compensation
• ROS2 integration connecting perception, estimation, and pan-tilt control
• Edge deployment, debugging, and iteration on Jetson-class hardware
• You will build for real constraints: latency budgets, live camera streams, imperfect sensors, outdoor field conditions, and fast field-test cycles.
• You will also help create the foundations around the stack: deployment workflows, data pipelines, evaluation tools, live telemetry, and the first steps toward space-payload operational requirements.

Requirements

• Production-level OpenCV, plus strong Python and C++
• ROS2 experience in real systems, not only tutorials or coursework
• Embedded or real-time camera pipeline experience, ideally with GStreamer or similar
• Practical experience with object detection, tracking, and live perception systems
• Hands-on state estimation experience, including EKF, UKF, or equivalent approaches
• A good feel for latency, threading, buffering, dropped frames, timestamps, and real-time system failure modes.
• You must have NATO member state citizenship.

Nice to have

• Experience with TensorRT, ONNX Runtime, Jetson Orin, CUDA, Docker on embedded hardware, robot localization, GNSS / RTK, NED / ENU frames, visual-inertial odometry, behaviour trees, state machines, or IR / thermal / near-IR imaging.
• Experience with small, fast-moving, or low-contrast targets such as drones, birds, aircraft, or distant moving objects is especially relevant.