Machine Learning Engineer

Salary: £40,000 - 67,000 per year

Requirements:

• Previous experience in tuning and deploying machine learning methods
• Experience with some of the following predictive modelling techniques: Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering
• Experience in DevOps and Azure ML, or other MLOps and ML lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc.
• Experience with deploying services in Docker and Kubernetes
• Experience in creating production-grade code and applying SOLID programming principles, including test-driven development (TDD) approaches
• Experience in programming languages such as Python, PySpark, R, SAS, or SQL
• Experience in source-control software, such as GitHub
• Proficient at communicating results concisely, both verbally and in writing
• Experience in data and model monitoring is a plus
• Educated to at least a masters level in a STEM-based or DS / ML / AI / or mathematical discipline
• Collaborative and team-oriented
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes

Responsibilities:

• Report and communicate with senior stakeholders, such as the Head of Data Science and Machine Learning and the Director of Technical Underwriting
• Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes and leverage DevOps and MLOps software
• Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible
• Tune machine learning methods for optimal performance
• Deploy and maintain machine learning methods in our machine learning pipeline using robust test-driven development (TDD) coding approaches and SOLID software development principles
• Actively contribute to creating a culture of coding and data excellence
• Implement efficient solutions across a range of markets, including Private Motor, Commercial Vehicle, Bike, Taxi, and Home
• Lead and mentor junior machine learning engineers and share best practices

Technologies:

• AI
• AWS
• Azure
• Cloud
• Databricks
• DevOps
• Docker
• GitHub
• Kubernetes
• Machine Learning
• MLOps
• Python
• PySpark
• SAS
• SQL
• TDD

More:

We are Markerstudy Group, a leading provider of private insurance in the UK, insuring around 5% of the private cars on UK roads, 20% of commercial vehicles, and over 30% of motorcycles, with total premium levels of circa £1 billion. Much of our business is written behind well-known brands such as Tesco, Sainsburys, O2, Halifax, AA, Saga, and Lloyds Bank. This is a hybrid role based in Manchester or Haywards Heath, and we offer the opportunity to work on leading-edge, novel insurance risk modelling and pricing techniques, while helping build fully automated machine learning pipelines. We provide a collaborative environment with opportunities to coach and mentor junior ML engineers and make a meaningful impact across our Motor, Home, and Commercial Lines businesses.

last updated 30 week of 2026