ML Ops Engineer | York Hybrid
- , , united kingdom, United Kingdom
- Hybrid
- £80 - £100 Per Hour
Job Description
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