MLOps Engineer: Production ML, Secure Data Pipelines

checkatrade; City Of London; Hybride; GBP 85 000 - 110 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Annual bonus & equity

Health & wellbeing

Gym membership

Cycle scheme

Holiday buy/sell

Charity leave

Résumé du poste

Checkatrade is seeking an experienced MLOps Engineer to own how machine learning and AI run in production. You will translate Data Scientists' models into live, reliable services and build secure foundations for AI tools and agents to use our data.

You will report to the Head of Data Engineering, collaborating with engineers and data scientists across platforms, ensuring reliability, security and cost control in a hybrid London-based role.

Qualifications

• Strong Python, with production deployment and monitoring experience.
• GCP experience with ML/data services.
• Docker and Kubernetes, plus CI/CD and IaC.
• Observability for ML/data systems: metrics and alerting.
• Security-minded data access and secrets management.
• Ownership of production systems and collaboration with DS/engineers.

Responsabilités

• Deploy, automate, monitor and retrain ML models, aiming for near real-time refresh where valuable.
• Set MLOps standards: CI/CD, model versioning and reusable patterns.
• Build infra to let AI tools access data securely.
• Keep GCP-based data platform reliable and secure; reduce debt.
• Monitor models, pipelines and platform services to catch drift and cost issues early.
• Apply controls to ML workloads, including data access lineage and reproducibility.

Connaissances

Python

GCP

Docker

Kubernetes

CI/CD

Observability

Outils

AWS MWAA

Airflow

Description du poste

Checkatrade is seeking an experienced MLOps Engineer to own how machine learning and AI run in production. You will translate Data Scientists' models into live, reliable services and build secure foundations for AI tools and agents to use our data.

You will report to the Head of Data Engineering, collaborating with engineers and data scientists across platforms, ensuring reliability, security and cost control in a hybrid London-based role.