Lead MLOps Engineer - Telematics

We're a digital insurance provider with ambitious plans to become the best and biggest in the UK market. We've made huge investments in our pricing and data capabilities over the past few years, along with nurturing our 4Cs culture.

We provide insurance for over four million customers, but we know there's even bigger opportunity out there - our Pricing, Data and Analytics community value curiosity, collaboration and constructive challenge.

We are always looking for new ideas and diverse perspectives to question established thinking and drive meaningful change. Great pricing is built on trust, innovation and precision, so our aim is to ensure customers receive a fair and accurate price based on their individual risk, supporting fair outcomes, while delivering sustainable and profitable growth for our company.

Pricing is more than just a number - it's a strategic capability. At the heart of Hastings is deep risk insight - continually improving how we assess, segment and price risk through data and analytics.

Job Title: Lead MLOps Engineer

Location: Bexhill/Leicester/London - Hybrid

Role overview

We are looking for an experienced MLOps Engineer who enjoys solving complex technical challenges and building the platforms, tooling, and processes that enable machine learning at scale. The Lead MLOps Engineer will design, build, and maintain the infrastructure that supports the full machine learning lifecycle, from feature generation and experimentation through to deployment, monitoring, and continuous improvement. You will play a key role in ensuring our predictive models and data products are reliable, scalable, and deliver measurable business value. This role sits within our new Telematics Data Value team, comprising data scientists, analysts, and engineers. We work to turn our telematics data into underwriting advantage, enabling market-beating prices for customers.

Key responsibilities

• Provide technical leadership on ML platform architecture, helping shape the tooling, standards, and operating model used to deliver machine learning across the organisation.
• Develop and maintain automated workflows for feature engineering, model training, testing, deployment, monitoring, and retraining.
• Partner with Data Scientists and Data Engineers, and ML Engineers to operationalise predictive models and data products.
• Establish best practices for ML observability, model performance monitoring, CI/CD, versioning, governance, and reproducibility.
• Improve the reliability, scalability, and efficiency of our machine learning and data platforms.
• Work with cloud-native technologies and infrastructure-as-code to support modern ML workloads.
• Present technical solutions and outcomes to engineering, operational, and commercial stakeholders.
• Evaluate emerging technologies and contribute to the team's engineering standards and best practices.

Essential skills/experience

• Strong Python skills and experience building and operating machine learning solutions in cloud environments.
• Experience with MLOps tooling and practices, including CI/CD, containerisation, orchestration, model deployment, monitoring, and infrastructure automation.
• Experience using SQL and working with large-scale data platforms.
• Familiarity with modern cloud platforms such as Azure, AWS, or GCP.
• Experience collaborating across teams of Data Scientists, Data Engineers, Software Engineers, Operational and Commercial stakeholders.
• Understanding of software engineering best practices including testing, version control, code review, and observability.

Personal Attributes

• Technical excellence complemented by a strong understanding of business outcomes.
• A problem-solver who enjoys building robust, scalable solutions to complex real-world challenges.
• Able to work independently, seeking support where needed, while collaborating effectively across multidisciplinary teams.
• Curious, pragmatic, and willing to challenge existing approaches in pursuit of better outcomes.
• Passionate about engineering quality, automation, and continuous improvement

Recruitment Process

• Recruitment screening call
• 1stRoundIntrowiththe hiring leader
• Case Study round - a mix of Technical and Competency

As a Disability Confident employer, we're committed to ensuring our recruitment processes are fully inclusive - what this means to you is if you're applying for a job with us, you'll have fair access to support and adjustments throughout your recruitment journey. We also welcome applications through the Disability ConfidentScheme(DCS).FormoreinformationontheDCS,pleasevisitour inclusive business page on our career's website

What we offer

Joinusandyou'llfindadifferentwayofdoingthings.Wecallitthe4Cs.Wefocusongettingitrightforourcolleaguestobedifferent.

Not to mention plenty of recognition and rewards, and

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