Computer Vision Engineer

About the job

ADB Safegate leads the world in smart solutions that help airports handle more aircraft, safely and efficiently, from approach to departure. Our products and services include runway and taxiway lighting; to tower-based traffic control systems; to intelligent gate and docking automation.

We are looking for talented and enthusiastic people with the passion to support our vision and help to change the future of our APRON Business. We are now offering a fascinating position as a CV Engineer to join our team.

Responsibilities

• Develop models for detection, segmentation, tracking, OCR, action recognition, and video analytics.
• Build video ingestion, annotation, augmentation, training, evaluation, and inference pipelines.
• Optimise models for near-real-time execution across cloud, data-centre, and edge platforms.
• Integrate model events, confidence, timestamps, and health status into operator monitoring workflows.
• Manage false positives, missed detections, model drift, changing weather, lighting, and camera conditions.
• Monitor production accuracy, latency, throughput, resource use, camera availability, and model health.

Requirements

• Bachelor’s or Master’s in Computer Science, AI, Electrical Engineering, Mathematics, or a related discipline.
• 5+ years of production experience in computer vision or deep learning.
• Strong Python and TensorFlow, PyTorch, or Keras skills.
• Strong experience with OpenCV and detection, segmentation, tracking, OCR, or video analytics.
• Experience with data preparation, model evaluation, deployment, monitoring, and MLOps.
• Experience with real-time, multi-camera, edge, NVIDIA, or mission-critical systems is preferred.

Soft Skills

• Strong analytical and experimental mindset.
• Clear understanding of the operational impact of false or missed alerts.
• Ability to communicate confidence, limitations, and model trade-offs.
• Strong collaboration with domain, software, verification, and MLOps teams.
• Disciplined approach to reproducibility and documentation.
• Ownership from experimentation through production operation.