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ML Ops Engineer | Hybrid

Job in York, North Yorkshire, YO90, England, UK
Listing for: Oliver James
Full Time position
Listed on 2026-05-30
Job specializations:
  • IT/Tech
    AI Engineer, Data Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below

Overview

We're building a new ML Engineering team and are looking for a strong technical lead to help take our machine learning capability from proof-of-concept to fully scaled, production-ready solutions.

Sitting within our Group & Enterprise Services (GES) function, this role is part of the Data vertical and reports into the Head of Data Engineering. You'll be hands-on with cloud infrastructure, APIs and deployment pipelines, working mainly in GCP Vertex AI (essential) and Azure (desirable). Your focus will be enabling data scientists to deploy high-impact models reliably and at scale.

You'll combine leadership, architectural thinking and deep engineering skills to shape the ML platform, coach engineers and deliver robust, enterprise-ready ML services.

What you'll do
  • Lead, mentor and develop a small team of ML Engineers
  • Oversee delivery of ML capabilities and support planning and capacity needs
  • Shape architecture from early design through to production
  • Build and maintain Python APIs (Flask/FastAPI) for model serving
  • Develop infrastructure for real-time and batch deployments
  • Design and maintain CI/CD pipelines for models
  • Ensure code quality, engineering best practice and scalable cloud deployments
  • Collaborate with data scientists, platform engineers and developers
  • Support model lifecycle management, monitoring and automation
  • Break down solution designs into deliverables and milestones
What you'll bring
  • 5+ years as an ML Engineer with strong Python engineering skills
  • Experience deploying and maintaining ML models in production (Vertex AI required)
  • Strong software engineering fundamentals: OOP, unit testing, TDD
  • Cloud experience (GCP, AWS or Azure) and IaC tools such as Terraform
  • Experience with Docker, CI/CD pipelines and Git workflows
  • Understanding of data science principles and taking research code to production
  • Strong problem-solving skills and the ability to work independently
  • Comfortable working in Agile teams
  • Clear communication, collaboration and a proactive, improvement-driven mindset
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