Computer Vision & AI Engineer - N3XT Interceptor C‑UAS (m/f/d)

About Quantum Systems

Quantum Systems specializes in the development, design, and production of small Unmanned Aerial Systems (sUAS). Our electric vertical take-off and landing (eVTOL) sUAS are engineered for maximum range and versatility, offering a seamless user experience. By integrating advanced software capabilities like edge computing and real-time AI-powered data processing, we are building next-generation UAS for defense, security, and public sector clients.

About The Role

We are seeking a Computer Vision & AI Engineer to drive the perception stack of our Counter-UAS interceptor platform. You will work on critical aspects such as 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. This role is ideal for individuals with a strong academic or practical background in computer vision, AI, robotics, or perception systems. A Master's degree is expected, and a PhD is a strong plus. Ambitious early-career candidates with deep technical expertise and practical implementation skills are also encouraged to apply.

Your Mission

Develop the vision and AI pipeline that transforms 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.
• Precision landing support.

Day-to-Day Responsibilities

• 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, combining machine learning and classical computer vision.
• Fuse inertial data, motion information, and visual data to enhance detection and tracking in moving image sequences.
• Build object tracking pipelines that transition from initial detection to low-latency tracking.
• Optimize perception pipelines for embedded execution on NVIDIA Jetson platforms, aiming for high frame rates (100–300 FPS).
• Utilize 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 forward-facing camera views.
• Develop visual support for precision landing, including height, velocity, and motion-state estimation.
• Build and maintain the data pipeline from onboard recordings to cloud storage, encompassing 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 (e.g., CenterNet, SuperPoint, SuperGlue, optical flow, feature tracking, object detection, 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.

What You Bring to the Team

• 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.

Bonus Points

• 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.

Why Join Quantum-Systems?

• 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.

How to Apply

Please include as your cover letter:

• A detailed description of your hands-on projects, including photos, GitHub links, and videos, drawings.