Our purpose is to make great financial decision making a breeze for everyone, and that purpose drives us every day.
It’s why we’re on a mission to create an automated quoting engine, with the simplest of experiences, wrapped in a brand everyone loves!
We change lives by making it simple to switch and save money and that’s why good things happen when you meerkat.
We’d love you to be part of our journey!
We’re scaling our AI capabilities at Compare the Market, and Machine Learning Engineering is at the core of how we turn models into production-ready systems. As a Machine Learning Engineering Manager, you’ll lead a team of MLEs responsible for building, deploying, and maintaining the ML infrastructure that powers our personalisation, optimisation, and intelligent decision-making products.
This is a hybrid role for a hands-on engineering leader—someone who can lead people, deliver at pace, and contribute to system design and platform standards. You’ll partner with data science, analytics, and platform engineering teams to accelerate how AI is developed and deployed across the organisation.
Everyone is welcome!
We have a culture of creativity. We approach our work passionately, improve constantly and celebrate our wins at every turn. We are an inclusive workplace and our employees are comfortable bringing their authentic, whole selves to work. Everyone is welcome. Be you.
This means we’re excited to hear from people with a range of skills, experiences and ideas. We don’t expect you to tick all the boxes, but would love to hear what makes you great for this role.
Some of the great things you’ll do:
Team Leadership & Delivery
• Lead a team of MLEs delivering robust, scalable machine learning systems into production
• Drive team planning, estimation, and sprint delivery—ensuring projects are delivered on time and to a high standard
• Support the development of real-time and batch ML workflows across a variety of business use cases
• Collaborate closely with data scientists to move prototypes into high-quality production systems
Platform & Engineering Standards
• Contribute to the design and evolution of our internal ML platform and tooling
• Champion best practices in CI/CD, observability, reproducibility, and infrastructure-as-code for ML
• Ensure all deployed systems meet requirements for resilience, testing, security, and performance
• Influence and contribute to shared frameworks, libraries, and deployment pipelines
Strategy & Cross-Functional Collaboration
• Work with technical and product leads to align team roadmaps to business goals
• Identify and unblock cross-team dependencies involving data science, platform, and software engineering
• Help shape platform direction by feeding back requirements from applied ML delivery
People & Culture
• Line manage and mentor MLEs, supporting their career development and technical growth
• Foster a culture of collaboration, feedback, and continuous improvement
• Lead hiring, onboarding, and team capability development initiatives
What we’d like to see from you:
• Experience leading engineering teams focused on machine learning, data platforms, or applied AI delivery
• Proven track record deploying ML systems in production at scale (batch and/or real-time)
• Strong technical background in Python and ML engineering tooling (e.g. MLflow, Airflow, SageMaker, Vertex AI, Databricks)
• Understanding of infrastructure-as-code and CI/CD for ML systems (e.g. Terraform, GitHub Actions, ArgoCD)
• Ability to lead delivery in agile environments—balancing scope, prioritisation, and quality
• Excellent communication and collaboration skills across technical and non-technical stakeholders
• A background in software engineering, MLOps, or data engineering with production ML experience
Nice to have:
• Familiarity with streaming or event-driven ML architectures (e.g. Kafka, Flink, Spark Structured Streaming)
• Experience working in regulated domains such as insurance, finance, or healthcare
• Exposure to large language models (LLMs), vector databases, or RAG pipelines
• Experience building or managing internal ML platforms, experimentation frameworks, or feature stores
There’s something for everyone.
We’re a place of opportunity. You’ll have the tools and autonomy to drive your own career, supported by a team of amazingly talented people.
And then there’s our benefits. For us, it’s not just about a competitive salary and hybrid working, we care about what matters to you. From a generous holiday allowance and private healthcare to an electric car scheme and paid development, wellbeing and CSR days, we’ve pretty much got you covered!
#LI-HL1
#J-18808-Ljbffr
