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Computer Vision & AI Engineer - N3XT Interceptor C‑UAS (m/f/d)
<h3>About the Role</h3><p>At Quantum Systems, we are building highly autonomous interceptor systems that must perceive, decide, and act under extreme latency, motion, and environmental constraints.</p><p>We are looking for a Computer Vision & AI Engineer to drive the perception stack of our Counter-UAS interceptor platform. You will work on low-latency camera pipelines, small-object detection, object tracking, sensor fusion, visual odometry, precision landing, camera calibration, embedded inference, and data pipelines for training and validation.</p><p>This role is suited for someone with a strong academic or practical background in computer vision, AI, robotics, or perception systems. A Master’s degree is expected; a PhD is a strong plus. We are open to ambitious early-career candidates if they bring strong technical depth, practical implementation skills, and the ability to own complex perception problems.</p><p>Your Mission</p><p>You will develop the vision and AI pipeline that turns raw camera data into actionable perception outputs for autonomous flight. This includes low-latency detection and tracking, motion-aware vision, sensor fusion with inertial data, 3D direction-vector estimation, GPS-denied navigation, and precision landing support.</p><p style=";"></p><h4 style=";"><strong>What is your Day to Day Mission:</strong></h4><ul><li><p>Bring up, optimize, and maintain high-performance camera pipelines, including CSI camera interfaces, raw image access, buffering, synchronization, and latency reduction.</p></li><li><p>Develop detection algorithms for small and difficult-to-see objects in moving and rotating camera images.</p></li><li><p>Combine machine learning and classical computer vision approaches where appropriate.</p></li><li><p>Fuse inertial data, motion information, and visual data to improve detection and tracking in moving image sequences.</p></li><li><p>Build object tracking pipelines that can switch from initial detection to low-latency tracking once a target has been acquired.</p></li><li><p>Optimize perception pipelines for embedded execution on NVIDIA Jetson platforms.</p></li><li><p>Work toward high frame-rate processing targets in the range of 100–300 FPS, where technically feasible.</p></li><li><p>Use camera intrinsics and extrinsics to transform image-space detections into 3D direction vectors or other navigation-relevant outputs.</p></li><li><p>Work on GPS-denied navigation concepts using visual odometry, including approaches with forward-facing camera views rather than only downward-looking cameras.</p></li><li><p>Develop ...