25 - Computer Vision Expert (CCTV & Video Analytics)

Role overview Develop and productionise computer vision systems that analyse live CCTV streams and large-scale video. The work combines classical image-processing techniques and machine learning to detect, track and analyse objects and events, then connect those capabilities with other applications. Real-time performance and accuracy are central concerns.

Responsibilities - Build computer vision algorithms for CCTV, including object detection, tracking and anomaly or event detection. - Integrate video analytics with connected applications and services. - Work with software teams to support efficient deployments across edge and cloud environments. - Measure and improve accuracy, latency and scalability for real-time use.

Requirements - A master’s or doctoral degree in computer science, electrical engineering, AI or a related field. - Demonstrated experience in computer vision, image or video processing, and machine learning. - Proficiency with tools such as TensorFlow, PyTorch and OpenCV. - Strong programming skills in Python and C++. - Working knowledge of streaming protocols such as RTSP and ONVIF. - Ability to solve problems using large, real-world video datasets.

Nice to have Experience with real-time CCTV analytics, edge computing, auto-labelling or model distillation, and optimisation for embedded systems or GPUs. Knowledge of cybersecurity and privacy considerations for video surveillance is also useful.