Senior MLOps & Computer Vision Architect

Nicholson Glover; England; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading sports data analytics company seeks a Senior MLOps & Computer Vision Architect for a 6-month contract. The role involves building a complete ML production pipeline on Azure, handling everything from data ingestion to model deployment. You will have true ownership of the architecture and a chance to make a significant impact in a fast-paced sports AI domain. This position starts in January 2026 and offers a competitive day rate with a hybrid work model, allowing for possible remote work in the UK.

Qualifications

• Strong experience with building production MLOps systems on Azure.
• Proven track record in designing data pipelines and automated model lifecycles.
• Experience deploying and optimising computer vision models like YOLO and Detectron.

Responsibilities

• Architect and build the cloud-native MLOps platform on Azure.
• Define strategies for tracking brand assets across videos.
• Develop the analyst verification interface for model outputs.
• Hand over documentation and architecture diagrams at project end.

Skills

MLOps systems on Azure

Data pipelines

Computer vision models

Annotation tools

Scalable inference systems

HITL tooling

Production systems

Job description

🚀 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.