Senior MLOps & Computer Vision Architect

🚀 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.

🎯 What You’ll Own (End-to-End)

1. MLOps & Azure Architecture

You’ll architect and build our entire cloud-native MLOps platform on Azure, including:

• High-throughput video processing infrastructure
• Robust data pipelines (Encord → Azure → Roboflow)
• Automated model training + versioning
• Deployment of high-performance inference services
• ETL pipelines to turn predictions into client-ready metrics

This is full system ownership — and you’ll be the one building it.

2. Computer Vision Strategy & Model Lifecycle

You will define how we track brand assets across sports video and social media content by:

• Designing the CV approach (models, data strategy, optimisation)
• Integrating Encord annotations with Roboflow training pipelines
• Deploying and optimising the model at scale
• Setting up monitoring to catch model drift before it becomes a problem

3. Human-in-the-Loop (HITL) Tooling

You’ll build the analyst verification interface that:

• Flags low-confidence detections
• Lets analysts quickly confirm/correct outputs
• Feeds improved data straight back into the training pipeline

This is the backbone of our continuous learning loop.

4. Knowledge Transfer

At the end of the project you’ll hand over:

• Documentation
• Architecture diagrams
• Runbooks
• Codebase walkthroughs

So our internal team can take full ownership.

🌟 Why This Role Is Special

• True ownership: You design it, you build it, you ship it.
• No legacy tech: Clean slate. You choose the right tools and architecture.
• Real-world impact: Your system will power visibility metrics used by global brands.
• Massive scope: MLOps, CV, cloud architecture, inference, ETL, HITL — all yours.
• Fast-moving domain: Sports + AI + video = one of the most exciting fields right now.

If you’re tired of being one engineer on a huge team and want to own the entire machine, this is your chance.

🔧 What We’re Looking For

You don’t need every keyword — but you should have strong experience with:

• Building production MLOps systems on Azure
• Designing data pipelines and automated model lifecycles
• Deploying and optimising computer vision models (YOLO, Detectron, etc.)
• Working with annotation tools (Encord, Labelbox, Roboflow, etc.)
• Creating scalable inference systems for video/image workloads
• Building HITL or internal analyst tooling
• Shipping production systems in fast-paced environments

This is a senior, hands-on architect role — ideal for someone who likes building things properly and getting things done.

📍 Contract Details

• 6-month contract (likely extension)
• Competitive day rate
• Hybrid initially then possible remote UK
• Start date: Jan 2026

📬 How to Apply

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.