Computer Vision & AI Engineer - Interceptor C‑UAS (m/f/d)

Your Mission

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.

What is your Day to Day Mission:

• Bring up, optimize, and maintain high-performance camera pipelines, including CSI camera interfaces, raw image access, buffering, synchronization, and latency reduction.
• Develop detection algorithms for small and difficult-to-see objects in moving and rotating camera images.
• Combine machine learning and classical computer vision approaches where appropriate.
• Fuse inertial data, motion information, and visual data to improve detection and tracking in moving image sequences.
• Build object tracking pipelines that can switch from initial detection to low-latency tracking once a target has been acquired.
• Optimize perception pipelines for embedded execution on NVIDIA Jetson platforms.
• Work toward high frame-rate processing targets in the range of 100–300 FPS, where technically feasible.
• Use camera intrinsics and extrinsics to transform image-space detections into 3D direction vectors or other navigation-relevant outputs.
• Work on GPS-denied navigation concepts using visual odometry, including approaches with forward-facing camera views rather than only downward-looking cameras.
• Develop visual support for precision landing, including height estimation, velocity estimation, and motion-state estimation from limited camera perspectives.
• Build and maintain the data pipeline from onboard recordings to cloud storage, preprocessing, annotation, dataset generation, training, validation, and benchmarking.
• Work with annotation tools such as SuperAnnotate, CVAT, Label Studio, or comparable systems.
• Benchmark and evaluate different model and algorithm families, including approaches such as CenterNet, SuperPoint, SuperGlue, optical flow, feature tracking, object detection, and lightweight embedded models.
• Build deployment pipelines using ONNX, TensorRT, custom inference runners, or comparable embedded inference tooling.
• Collaborate closely with autonomy, flight control, embedded software, test, and systems engineering teams.

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.

• Master’s degree or PhD in computer vision, AI, robotics, machine learning, electrical engineering, computer science, aerospace engineering, or a comparable technical field.
• Strong understanding of computer vision fundamentals, camera geometry, feature detection, object detection, tracking, calibration, and image-space to 3D transformations.
• Practical experience implementing computer vision or machine learning pipelines in Python and C++.
• Experience with embedded inference, ideally on NVIDIA Jetson, CUDA, TensorRT, ONNX, GStreamer, V4L2, or similar technologies.
• Ability to read, understand, and implement ideas from current research papers.
• Understanding of latency, throughput, profiling, memory movement, and real-time constraints.
• Experience with dataset creation, annotation workflows, training/validation splits, metrics, and benchmarking.
• Strong mathematical intuition and willingness to debug both algorithms and real-world sensor data.
• Ability to take ownership of a technical area and drive it from research prototype to flight-test-ready software.
• Experience with UAV perception, robotics perception, visual odometry, SLAM, sensor fusion, or tracking systems.
• Experience with IMU-camera fusion, ego-motion compensation, rolling-shutter effects, or high-frame-rate cameras.
• Experience with precision landing, visual navigation, or GPS-denied navigation.
• Experience building cloud-based ML training and validation pipelines.
• Publications, thesis work, GitHub projects, demos, or competition results in computer vision, robotics, AI, or autonomous systems.

We offer

• Be at the forefront of next-generation Defence innovation.
• Work in a fast-paced, agile environment where your ideas make an impact.
• Collaborate with a team of industry pioneers who are ambitious, bold, and visionary.
• Opportunities for individual and professional growth in a globally recognized organization.

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.