Computer Vision Engineer
We are currently looking for a Computer Vision Engineer for our client - an innovative company working on advanced UAV technologies and autonomous aerial systems.
The role focuses on developing and optimizing perception algorithms for UAV platforms, with an emphasis on real-time detection, classification, tracking, vision-based pose estimation, EO/IR sensor fusion, and edge deployment under strict latency, power, and memory constraints in safety-critical, defense-grade environments.
Responsibilities
Computer Vision & Perception:
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Design and implement real-time object detection, classification, multi-target tracking, and change detection for autonomous UAV operations, including high-altitude ground target detection, camouflage, and foliage occlusion.
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Optimize deep learning models (YOLO, transformers, CNNs, or proprietary architectures) for edge deployment on embedded platforms (NVIDIA Jetson, Qualcomm RB5) under strict latency, power, and memory budgets.
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Develop vision-based pose estimation, optical flow, and feature tracking pipelines for mission-critical applications.
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Implement camera calibration routines and multi-camera rig setups for stereo and wide-baseline configurations.
Sensor Fusion for Perception:
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Develop sensor fusion pipelines combining EO/IR (thermal/FLIR), depth, and RF data to produce robust environment representations across day/night and degraded conditions.
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Implement probabilistic fusion approaches (complementary filters, tightly-coupled vision-IMU) to maintain perception reliability under low light, motion blur, and occlusion. Integration & Validation:
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Integrate perception pipelines with ROS2-based software stacks and companion computers (Jetson, RB5).
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Benchmark algorithms in simulation (Gazebo, MATLAB/Simulink) and HIL/HITL testbeds; validate through field trials.
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Measure and report KPIs (detection accuracy, latency, false-positive rate, robustness under environmental variation) and iterate on improvements.
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Document algorithm designs, performance characteristics, and integration interfaces; support certification efforts.
Qualifications
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Master's or PhD in Computer Science, Electrical Engineering, Robotics, or related field.
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3+ years developing computer vision algorithms for real-world autonomous systems (UAVs, robotics, or autonomous vehicles).
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Proven expertise in object detection, tracking, feature extraction, visual odometry, and camera calibration.
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Proficiency in C++ and C (OpenCV, Eigen) and Python (NumPy, SciPy, scikit-learn, scikit-image).
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Hands-on experience with detection and segmentation frameworks (YOLOv8+, Detectron2, MMDetection, Mask R-CNN, U-Net).
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Advanced use of PyTorch, TensorFlow/Keras, and ONNX for model training and export.
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Experience deploying and optimizing models on embedded platforms (Jetson, Qualcomm RB5, ARM).
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Experience with EO/IR sensor stacks: thermal (FLIR/uncooled) camera integration, NUC calibration, and thermal-domain object detection.
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Strong mathematical foundation in linear algebra, probability theory, and optimization.
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Solid version control practices (Git/GitLab) and dataset/model management (DVC or equivalent).
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English: Upper Intermediate or higher.
Will be a plus
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Proficiency in ROS2: node development, sensor integration, message pipelines.
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Experience with edge AI optimization: quantization, pruning, model compression for TensorRT, ONNX Runtime, OpenVINO.
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Familiarity with annotation platforms (Label Studio, Labelbox) and experiment tracking tools (MLflow, Neptune.ai, TensorBoard).
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Knowledge of tightly-coupled vision-IMU fusion (VINS-Mono, Kimera) for perception-side pose estimation.
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Familiarity with safety-critical standards: DO-178C (avionics software), MISRA C/C++ coding guidelines,
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STANAG 4671 (UAV airworthiness) as applied to perception pipelines used in flight-critical decisions.
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Track record of publication at CVPR, ICRA, IROS, or IEEE Transactions, or contributions to open-source CV repositories.
What We Offer
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Office-based work in Luxembourg (5 days per week).
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Relocation assistance.
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26 days of paid vacation.
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Medical insurance and sick leave covered by the Luxembourg national healthcare system.
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Clear work-life balance policy with no overtime culture.