Lead Machine Learning & AI Engineer - 10 month Fixed Term Contract

First Central

7d•Hybrid

About The Position

At 1st Central, everything starts with our people. As one of the UK’s leading motor and home insurers, we use smart technology, data and great service to make insurance fast, fair and simple for over 1.4 million customers. We’re proud to create an environment where people feel supported, trusted and able to grow - whether that’s developing new skills, taking on fresh challenges or making a real impact every day. If you’re looking for a role where you can make a difference, we’d love to hear from you. We’re on the hunt for a Lead Machine Learning & AI Engineer to join our Data & Analytics function on a 10-month fixed term contract, where you’ll play a pivotal role in implementing and continuously improving the machine learning and AI operations frameworks that bring innovative solutions to life across our organisation. You’ll design and deliver new tools, components of the framework and engineering practices that turn cutting‑edge models into high‑performing, production‑ready systems. In this highly collaborative role, you’ll coach and guide a small team of Machine Learning Operations Engineers, Analytics Engineers and AI Engineers while working closely with colleagues across Data Science, Pricing, Data Engineering and Software Development. Together, you’ll ensure our machine learning and AI models are engineered with excellence, from raw data through to seamless integration into real‑world business processes. This is a flexible hybrid role, where you'll predominantly be home-based, with just one day per month in the office, either in Salford Quays (Manchester), Haywards Heath (West Sussex) or Guernsey. If you'd like to spend more time collaborating with the team, you're welcome to work from the office more frequently.

Requirements

Azure Cloud & AI Platform Expertise: Deep experience and strong understanding of Microsoft Azure (Azure ML, Azure Stream Analytics, Cognitive Services, Event Hubs, Synapse, and Data Factory).
Data Science & AI Development Skills: Fluency in Python and common modelling frameworks such as PyTorch and TensorFlow.
MLOps & Production Deployment: Skilled in applying MLOps frameworks within production environments.
Analytical & Problem‑Solving Strength: Excellent problem-solving and analytical skills.
Troubleshooting & Technical Diagnosis: Ability to diagnose and troubleshoot problems quickly.
Strong line management: Ability to effectively run and manage a team, motivating for high performance and managing under-performance where necessary.
Extensive experience of building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer.
Experience building integrations between cloud-based systems using APIs.
Experience developing and maintaining ML and AI systems.
Experience of agile ways of working, applied in a data science, machine learning and AI environment.
Experience of designing, or maintaining data software development lifecycles, and continuous integration and deployment (CICD).
Exposure to machine learning and AI methodology and best practices.
Coaching experience.
Deep experience and strong understanding of Microsoft Azure, (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory).
Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, TensorFlow etc.
Skilled in application of MLOps frameworks within a production environment.
Excellent communication skills, both verbal and written.
Strong time management and organisation skills.
Ability to diagnose and troubleshoot problems quickly.
Excellent problem-solving and analytic skills.
Strong stakeholder management.
Leads by example, encouraging others to fulfil their potential.
Embrace, embed and incorporate the company values.
Self-motivated and enthusiastic.
An organised and proactive approach.
Ability to work on own initiative and as part of a team.
A flexible approach and positive attitude.
Strives to drive business improvements to contribute to the success of the business.

Nice To Haves

Experience within financial/insurance services industry advantageous

Responsibilities

Continue to grow and evolve our Machine Learning & AI Engineering standards and frameworks.
Design further enhancements to the data pipelines and engineering infrastructure to embed scaled machine learning & AI solutions.
Support data science and AI discovery and model development activities, through acquisition and transformation of data.
Support model development, with an emphasis on auditability, versioning, and data security.
Collaboratively design and implement AI Ops on cloud (Azure).
Optimise deployment of ML & AI model scoring code in production services.
Use CI/CD pipelines, manage the deployment and version management of large numbers of data science & AI models, supporting customer and operational processes.
Protect against model degradation and operational performance issues through the development and continual automated monitoring of model execution and model quality.
Manage the remediation of priority 2, 3 and 4 issues impacting production ML & AI services deployed within the business.
Carry out data science & AI model testing, validation and test automation.
Support deployment of ML & AI models as API endpoints for consumption within First Central and partner systems.
Continually look for how we can evolve and improve our technology, processes and practices.
Lead group discussions on system design and architecture and sharing knowledge with the wider engineering community.
Collaborate closely with data scientists, data engineers, AI engineers, and the software development team to ensure end to end data science and AI solutions are embedded into business processes.
Liaise with senior stakeholders across the business to ensure ML and AI are being used to improve strategic business decisions and identify new areas for improvements.
Provide coaching, empowerment and support to a team of ML Ops and AI engineers.
Comply with the requirements, and act in accordance with, the Group Code of Conduct and Fitness and Propriety policies at all times.
Ensure compliance with Company Policies, Values and guidelines and other relevant standards/ regulations at all times.