Machine Learning Engineering Manager

Machine Learning Engineering Manager

Function: Data & AI Solutions

Location: Hybrid, London office

So are we. Join Compare the Market and help to make financial decision making a breeze for millions.

At Compare the Market, we’re a purpose‑driven business powered by tech and AI. We’re building high‑performing, results‑driven teams with the skills, mindset, and ambition to deliver outcomes ry role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.

We’ve carved a meerkat‑shaped niche and we’re looking for ambitious, curious thinkers who thrive in a fast‑moving, high‑impact environment. If you love accountability, embrace challenge, and want to make a real difference, you’ll fit right in.

Compare the Market is at an inflection point. We are shifting from a business that answers data questions to one that builds the intelligence powering our AI systems and platform.

As a Machine Learning Engineering Manager in our Data & AI Solutions team, you will lead a team building and owning production systems at the heart of our AI platform. That means real‑time inference APIs serving millions of customers, batch data products powering intelligent decision‑making, and LLM‑based agentic solutions spanning both customer‑facing products and internal tools that shape how the wider team works.

These are not simple systems – and building them well, keeping them healthy, and continuously raising the engineering bar is what this team exists to do.

You will set technical direction, develop your team, and work closely with data, product, commercial and engineering colleagues to ensure the intelligence your team builds has a real effect on the business.

• Lead and develop a team of ML engineers, creating the conditions for them to deliver robust, scalable systems into production – spanning real‑time inference APIs, batch data products, and LLM‑based agentic solutions
• Collaborate closely with data scientists to move prototypes into high‑quality production systems, maintaining quality and performance as complexity scales
• Drive team planning, estimation, and sprint delivery – ensuring projects are delivered on time and to a high standard
• Ensure every system your team ships connects to a real outcome and has a mechanism to improve over time

• Develop your team of machine learning engineers through regular feedback, technical mentorship and honest career conversations
• Contribute to hiring, helping bring in people who combine technical rigour with curiosity and commercial awareness
• Foster a team environment where ambition and delivery reinforce each other
• Contribute to standards and practices across the wider Data & AI Solutions chapter

• Set the standard for ML and AI engineering quality, reproducibility, and production‑readiness across your team – covering model pipelines, deployment tooling, system design, and lifecycle automation
• Take ownership of how the team approaches production health: knowing when a system is degrading, having a plan to address it, and ensuring monitoring and observability are built in from the start
• Contribute to the design and evolution of our ML and AI tooling and shared platform components
• Be hands‑on in design sessions, code reviews, and architectural decisions where your input matters
• Guide your team through a fast‑moving tooling landscape spanning classical ML, LLM‑based systems, and agentic AI patterns – knowing when each is the right approach
• Champion responsible, auditable AI – particularly important in a regulated financial services environment where precision and explainability are non‑negotiable
• Encourage and model the use of AI‑assisted development tools within your team, and be actively curious about how automated coding and workflow tools can increase the pace and quality of your team’s output

• Work closely with data, product, commercial and engineering leads to translate strategic priorities into well‑scoped work
• Represent your…