AI Computer Vision Engineer

We are seeking a talented AI Computer Vision Engineer to build and deploy a next-generation video intelligence platform.

This is a standalone, hands-on engineering role where you will take ownership of the design, development and deployment of computer vision and machine learning solutions operating across edge and cloud environments. You will have the opportunity to shape the technical direction of the platform and bring innovative AI solutions from concept through to production.

Key Responsibilities

• Design and develop AI-powered computer vision solutions.
• Build and optimise machine learning models for video analytics.
• Train, validate and improve AI models using video datasets.
• Develop Python-based applications, APIs and supporting services.
• Support deployment of AI workloads on edge computing devices and cloud platforms.
• Participate in proof-of-concept initiatives, pilot deployments and production rollouts.
• Collaborate with stakeholders and technology partners to deliver innovative AI solutions.

What You'll Bring

• 3-5+ years experience in AI, Machine Learning or Computer Vision.
• Experience with OpenCV.
• Experience with TensorFlow, PyTorch or similar frameworks.
• Experience developing and deploying computer vision models.
• Understanding of object detection, image classification and video analytics.
• Experience working with large datasets and model training.
• Strong analytical and problem-solving skills.

Nice to Have

• Experience with YOLO models.
• Experience with edge AI or GPU-accelerated environments.
• Experience with Docker and containerised applications.
• Familiarity with Azure, AWS or Google Cloud.
• Experience deploying machine learning models into production environments.
• Experience with video streaming technologies.
• Understanding of MLOps concepts and tooling.

Ideal Candidate

The ideal candidate has successfully built and deployed practical AI solutions and enjoys solving real-world problems using computer vision and machine learning. We value demonstrated capability, curiosity and a hands-on approach more than years of experience alone.