Job Description

We're partnering with a data-driven technology company that's investing heavily in advanced video analytics. They're looking for a Lead Computer Vision Engineer to join a growing data function and take ownership of how large-scale video data is transformed into structured, high-value insights.
This is a high-impact role sitting at the intersection of computer vision, data engineering, and applied analytics. You'll be the most senior CV specialist in the organisation, setting technical direction and helping move an existing semi-manual workflow towards a highly automated, reliable, production-grade pipeline.
If you enjoy solving messy real-world problems, owning systems end to end, and seeing your work directly influence business outcomes, this role offers a lot of autonomy and responsibility.
Tasks

• Designing, building, and deploying production-ready computer vision pipelines that extract structured events and signals from long-form, variable-quality video footage
• Scaling and automating processing systems across large archives of historical video, while also supporting near-real-time use cases
• Reducing manual intervention by identifying opportunities for automation and system improvement
• Defining validation frameworks, metrics, and monitoring to ensure model accuracy and reliability
• Working closely with domain experts to define rules, edge cases, and quality thresholds
• Acting as the technical authority for computer vision, influencing architecture, standards, and long-term strategy
• End-to-end ownership: Take systems from early design through to deployment, monitoring, and iteration
• Technical leadership: Own architectural decisions and guide the evolution of the computer vision platform
• Quality and reliability: Build robust validation and monitoring to ensure outputs can be trusted at scale
• Strategic impact: Shape how computer vision is applied across the business as the function matures

Requirements

• Proven commercial experience building and deploying computer vision systems in production
• Strong hands-on experience in areas such as object detection, tracking, temporal event detection, pose estimation, or action recognition
• Excellent Python skills and experience with common CV/ML libraries such as OpenCV, PyTorch, or TensorFlow
• Experience owning technical and architectural decisions for data-intensive systems
• A pragmatic, delivery-focused mindset with the ability to balance experimentation and production reliability

Nice to have

• Experience working with noisy, imperfect real-world video data (e.g. broadcast or user-generated footage)
• Exposure to MLOps practices and tooling for deploying and monitoring models at scale
• Familiarity with sports, media, or broadcast video analytics

Benefits

• Up to 30% bonus.
• Enhanced pension contributions
• Private health insurance and life assurance
• Sabbatical option after five years
• 33 days' annual leave (including bank holidays)
• The opportunity to work on technically challenging, high-impact systems that directly influence business performance

OpenSource

Skills Required