Computer Vision Engineer

3+ years of experience
Luxembourg
Fulltime, Onsite

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:
 

  • 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.

  • 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.

  • Develop vision-based pose estimation, optical flow, and feature tracking pipelines for mission-critical applications.

  • Implement camera calibration routines and multi-camera rig setups for stereo and wide-baseline configurations.
     

Sensor Fusion for Perception:
 

  • Develop sensor fusion pipelines combining EO/IR (thermal/FLIR), depth, and RF data to produce robust environment representations across day/night and degraded conditions.

  • Implement probabilistic fusion approaches (complementary filters, tightly-coupled vision-IMU) to maintain perception reliability under low light, motion blur, and occlusion. Integration & Validation:

  • Integrate perception pipelines with ROS2-based software stacks and companion computers (Jetson, RB5).

  • Benchmark algorithms in simulation (Gazebo, MATLAB/Simulink) and HIL/HITL testbeds; validate through field trials.

  • Measure and report KPIs (detection accuracy, latency, false-positive rate, robustness under environmental variation) and iterate on improvements.

  • Document algorithm designs, performance characteristics, and integration interfaces; support certification efforts.


 

Qualifications

 

  • Master's or PhD in Computer Science, Electrical Engineering, Robotics, or related field.

  • 3+ years developing computer vision algorithms for real-world autonomous systems (UAVs, robotics, or autonomous vehicles).

  • Proven expertise in object detection, tracking, feature extraction, visual odometry, and camera calibration.

  • Proficiency in C++ and C (OpenCV, Eigen) and Python (NumPy, SciPy, scikit-learn, scikit-image).

  • Hands-on experience with detection and segmentation frameworks (YOLOv8+, Detectron2, MMDetection, Mask R-CNN, U-Net).

  • Advanced use of PyTorch, TensorFlow/Keras, and ONNX for model training and export.

  • Experience deploying and optimizing models on embedded platforms (Jetson, Qualcomm RB5, ARM).

  • Experience with EO/IR sensor stacks: thermal (FLIR/uncooled) camera integration, NUC calibration, and thermal-domain object detection.

  • Strong mathematical foundation in linear algebra, probability theory, and optimization.

  • Solid version control practices (Git/GitLab) and dataset/model management (DVC or equivalent).

  • English: Upper Intermediate or higher.


 

Will be a plus 

 

  • Proficiency in ROS2: node development, sensor integration, message pipelines.

  • Experience with edge AI optimization: quantization, pruning, model compression for TensorRT, ONNX Runtime, OpenVINO.

  • Familiarity with annotation platforms (Label Studio, Labelbox) and experiment tracking tools (MLflow, Neptune.ai, TensorBoard).

  • Knowledge of tightly-coupled vision-IMU fusion (VINS-Mono, Kimera) for perception-side pose estimation.

  • Familiarity with safety-critical standards: DO-178C (avionics software), MISRA C/C++ coding guidelines,

  • STANAG 4671 (UAV airworthiness) as applied to perception pipelines used in flight-critical decisions.

  • Track record of publication at CVPR, ICRA, IROS, or IEEE Transactions, or contributions to open-source CV repositories.


 

What We Offer

 

  • Office-based work in Luxembourg (5 days per week).

  • Relocation assistance.

  • 26 days of paid vacation.

  • Medical insurance and sick leave covered by the Luxembourg national healthcare system.

  • Clear work-life balance policy with no overtime culture.

Attach a CV file (PDF, DOC)

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