Machine Learning - Engineering Director
New Yesterday
Its why were on a mission to create an automated quoting engine, with the simplest of experiences, wrapped in a brand everyone loves!
Were 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, youll 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 leadersomeone who can lead people, deliver at pace, and contribute to system design and platform standards. Youll partner with data science, analytics, and platform engineering teams to accelerate how AI is developed and deployed across the organisation.
Lead a team of MLEs delivering robust, scalable machine learning systems into production
Drive team planning, estimation, and sprint deliveryensuring 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
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
Line manage and mentor MLEs, supporting their career development and technical growth
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. Ability to lead delivery in agile environmentsbalancing scope, prioritisation, and quality
A background in software engineering, MLOps, or data engineering with production ML experience
Familiarity with streaming or event-driven ML architectures (e.g. Exposure to large language models (LLMs), vector databases, or RAG pipelines
Experience building or managing internal ML platforms, experimentation frameworks, or feature stores
Youll have the tools and autonomy to drive your own career, supported by a team of amazingly talented people.
For us, its 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, weve pretty much got you covered!
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- Location:
- London
- Job Type:
- FullTime
