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A leading sports data analytics company is looking for a Senior MLOps & Computer Vision Architect. You will be responsible for architecting and building the entire MLOps pipeline on Azure, from data ingestion to inference. This role offers true ownership of projects with no legacy tech, all while having a real-world impact in sports. The position is for a 6-month contract with a competitive day rate, starting in January 2026, hybrid initially with potential for remote work within the UK.
🚀 Senior MLOps & Computer Vision Architect
6-Month Contract | Build the Entire Production Pipeline | Azure | Sports AI
Are you a senior MLOps or Computer Vision engineer who loves owning the whole pipeline end to end ?
Do you want to build something from scratch , move fast, and see your work in production within months...not years?
If so, this is the role.
We’re a leading sports data analytics company using computer vision to analyse live and on-demand sports footage and measure brand visibility. Our clients rely on our platform to understand the true value of global sponsorship deals.
We’re now looking for a hands‑on Architect / Engineer to own the full build of our next‑generation ML pipeline — from data ingestion through to inference, metrics and human‑in‑the‑loop feedback.
This is a rare opportunity to design, build, and ship a complete production system, not just contribute to part of one.
You’ll architect and build our entire cloud‑native MLOps platform on Azure, including :
This is full system ownership — and you’ll be the one building it.
You will define how we track brand assets across sports video and social media content by :
This is the backbone of our continuous learning loop.
So our internal team can take full ownership.
If you’re tired of being one engineer on a huge team and want to own the entire machine , this is your chance.
You don’t need every keyword — but you should have strong experience with :
This is a senior, hands‑on architect role — ideal for someone who likes building things properly and getting things done.
If you’re excited by building an entire ML platform from scratch — and want your work to power sponsorship decisions for global brands — we’d love to speak with you.