MLOps Engineer

We started as the place to find a trusted trade. Now, as we shape the future of home improvement, we're building the tech to transform that landscape for everyone - better products, smarter data, AI where it actually helps - so trades can spend less time on admin and consumers can find someone they trust, first time. That's Powering Great Work, and it's why every team here exists:
Trades spend less time on admin and more on winning work and growing their business
Homeowners get a trusted trade, first time, every time
We get to build products that change homes and lives across the country
As our next MLOps Engineer, you'll own how machine learning and AI run in production at Checkatrade. You'll turn our Data Scientists' models into live, reliable services, and build the secure foundations that let AI tools and agents use our data. You'll report to the Head of Data Engineering, in Barcelona (on-site) or London (hybrid).
The job, unfiltered:
Deploy, automate, monitor and retrain ML models, moving refresh frequency towards real-time where it adds value.
Set the MLOps standards for the Data Science team: CI/CD, model versioning and reusable patterns that save everyone reinventing the wheel.
Build the infrastructure that lets AI tools and agents (including Claude, MCP services and knowledge bases) access Checkatrade data securely.
Help keep our GCP-based data platform (with some infrastructure in AWS) reliable and secure, and chip away at legacy and technical debt.
Watch models, pipelines, AI usage and platform services, so drift, reliability and cost issues get caught early.
Apply the right controls to ML and AI workloads, including sensitive-data access, lineage and reproducibility.

Strong Python, with proven experience deploying, serving and monitoring ML models in production.
Hands-on experience with GCP and its ML and data services.
Docker and Kubernetes, plus CI/CD and infrastructure-as-code.
Experience building observability for ML or data systems: metrics, alerting and cost monitoring.
A security-minded approach to data access and secrets management.
You take ownership of production systems and care about them long after launch, and you work well with Data Scientists and engineers alike.
You favour simple, maintainable solutions and raise the engineering bar around you.

Feature stores, model registries and drift detection.
AWS experience, particularly managed Airflow (MWAA).
(Don't self-select out because you don't tick every box. We'd rather meet you.)
What you get
Competitive salary, annual bonus & equity scheme
Health, wellbeing and learning support
Gym membership, Smart Tech Scheme, Cycle Scheme
Birthday/special day leave, buy & sell holiday scheme
️ 1 week's paid charity leave, and more
How this goes
Screening call with one of our Talent Acquisition Partners
Interview with the hiring manager and members of the team