Machine Learning Engineer - York Hybrid

Machine Learning Engineer

Location: York - Hybrid Working

Contract: Permanent

Salary: £70,000

We're looking for a talented and pragmatic Machine Learning Engineer to join a growing Data Science team. This is an exciting opportunity to work on a diverse range of greenfield projects from fraud detection to generative AI where you'll have the freedom to shape solutions from the ground up.

In this role, you'll own the full machine learning lifecycle, collaborating closely with data scientists, software engineers, and business stakeholders to deliver scalable, production-ready solutions. You'll play a key part in ensuring research-driven models successfully transition into robust, enterprise-grade systems within a modern, cloud-native environment.

Responsibilities:

• Contribute to the evolution of our Data Science platform, defining ML Engineering best practices, tooling and architecture as our team and portfolio grow.
• Drive automation across the end-to-end data science lifecycle using CI/CD and infrastructure-as-code to support scalable production workflows.
• Collaborate across the full model development and deployment lifecycle, spanning traditional ML and generative AI solutions.
• Work closely with data engineers, software engineers and wider business teams to deliver impactful, production-ready ML services.
• Write clean, maintainable, high-quality Python code following industry best practices.
• Influence modelling approaches and contribute to technical design discussions, deployment strategies, and solution architecture.

Skills & Experience

• Proven experience in ML engineering or data science within a commercial or enterprise environment
• Strong Python programming skills and solid software engineering foundations
• Excellent communication skills, capable of explaining technical concepts to non-technical audiences
• Good understanding of core data science principles and modelling approaches
• Experience deploying ML services into production using cloud-native technologies (e.g., containers, Kubernetes or equivalent)
• Experience with Azure and/or Databricks is highly desirable
• Comfortable working with standard engineering and data tooling: Git, CI/CD pipelines (Azure DevOps a plus), JIRA
• Experience deploying ML solutions in regulated industries (finance, insurance, etc.) is advantageous
• Exposure to LLMs, generative AI or agentic AI in a commercial setting is a bonus

If You're passionate about applying data and engineering best practices to solve real-world problems, and you thrive in collaborative, cross-functional teams while working with emerging AI technologies this role would be perfect for you!

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