Lead Machine Learning Engineer

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Policy Expert – Lead Machine Learning Engineer 

🚀Are you ready to transform the insurance industry? 

Policy Expert is a forward-thinking business that loves to get things done. Leveraging proprietary technology and smart data, we offer reliable products and a wow customer experience. 

Having achieved rapid growth since being founded in 2011, we’ve won over 1.5 million customers in Home, Motor and Pet insurance and have been ranked the UK’s No.1-rated home insurer by Review Centre since 2013. 🏆 

Hear from our team about what it's like working at Policy Expert ✨ 

About our Machine Learning Team 

This is an exciting moment in our journey as we scale our AI capabilities to support ambitious growth across the business. We’re rapidly expanding our Data Science function and investing in the platforms that enable our teams to move fast and deliver impact. At the heart of this is our MLOps platform which is designed to empower Data Scientists to seamlessly experiment, iterate, deploy and monitor models in production. With access to modern, cutting-edge technologies, our goal is to build a best-in-class MLOps platform that accelerates innovations and turns great ideas into real-world solutions that have a genuine business impact. 

Your day to day: 

As our Lead Machine Learning Engineer, you’ll be at the centre of building the ML platform that powers our next wave of AI driven products. You’ll design and ship scalable, reusable infrastructure in GCP that enables Data Scientists to experiment quickly and get models into production with confidence. You’ll say hands-on while leading and mentoring a team of Machine learning Engineers, helping them grow technically and professionally. Working closely with Data Science and product teams, you’ll bridge the gap between experimentation and reliable production systems. This role is perfect for someone loves building things, moving quickly, and combining deep engineering work with growing and leading a team: 

• Design, implement and standardise end-to-end machine learning pipelines using Vertex AI Pipelines, Model Registry, and Cloud Run, with a strong focus on reliability, automation, and cost efficiency.
• Build reusable components and templates to accelerate model delivery across squads (training, evaluation, registry, monitoring).
• Develop MLOps frameworks and SDKs around metadata tracking, feature versioning, model governance, and CI/CD integration (e.g. Cloud Build, Terraform, GitHub Actions).
• Optimise data processing and orchestration using BigQuery, Cloud Composer and Pub/Sub
• Act as a bridge between Data Science, Product, and Platform teams to ensure smooth delivery of ML solutions
• Review architecture, design decisions, and code to maintain high engineering standards
• Foster a culture of engineering excellence, collaboration, and continuous learning within the team.
• Stay close to emerging trends in ML systems, generative AI, and agents; evaluating their fit within the MLOps landscape.

Who are you: 

• A degree in Computer Science, Software Engineering, Data Science or another quantitative field
• 6+ years of experience in building and deploying ML systems
• Able to balance being a hands-on Engineer while also leading or mentoring a team of Engineers
• Strong communicator who can work effectively with Data Scientists, Product Managers and Engineering teams
• Highly proficient in Python: writing clean, testable, modular code suitable for CI/CD environments
• A track record of designing MLOPs or ML platform tooling, not just consuming it.
• Strong understanding of model lifecycle automation, including reproducibility, validation, drift detection and rollback strategies
• Solid grasp of containerisation and infrastructure-as-code (Docker, GCP, IAM)
• A collaborative, pragmatic mindset and very comfortable discussing architecture with Engineers, Data Scientists and non-technical stakeholders
• Familiar with neural network frameworks such as PyTorch with an interest in GenAI or agentic workflows (LangChain, Vertex AI Agents, etc…) is a plus
• Knowledge of the industry would be a plus but not essential

Benefits: 

📍 This role will be based in our London office in a 50/50 Hybrid mode. 

💸 We match your pension contributions up to 7% 

🏥 Private medical & Dental cover 

📚 Learning budget of £1,000 a year + Study leave (with encouragement to use it) 

😁 Enhanced maternity & paternity  

🚉 Travel season ticket loan 

🎟️ Access to a wide selection of London O2 events and use of a Private Lounge 

🌈 Employee Wellbeing Programme 

🚪 Prayer room in Office 

What We Stand for and Next Steps“We pride ourselves on being an equal opportunity employer. We treat all applications equally and recruit based solely on an individual’s skills, knowledge, and experience. The quality and growing diversity of our team is a testament to this commitment”  

At Policy Expert, we are committed to fostering an inclusive and supportive environment for all candidates. If you require any reasonable adjustments during the interview process to accommodate your needs, please do not hesitate to let us know. We are dedicated to ensuring every candidate has an equal opportunity to succeed and will work with you to provide the necessary support. 

We aim to be in touch within 14 working days of your application – you will be notified if successful or unsuccessful. Please be encouraged to apply even if you do not meet all the requirements. 

Useful links: 

Glassdoor | Trust Pilot