MLOps Engineer

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).

Responsibilities

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; Build the infrastructure that lets AI tools and agents (including Claude, MCP services and knowledge bases) access Checkatrade data securely; Help keep the 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

Requirements

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

Nice to have

Streaming or event-driven systems for real-time inference; LLM and agent infrastructure (MCP, retrieval-augmented generation, vector stores); Feature stores, model registries and drift detection; AWS experience, particularly managed Airflow (MWAA)

Benefits

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