Staff ML Engineer

New Today

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!
As a Staff Machine Learning Engineer, you’ll play a pivotal role in designing, scaling, and evolving the machine learning infrastructure that powers Compare the Market’s most ambitious AI products. From LLM-based personalisation to real-time optimisation systems, you’ll help define how models are developed, deployed, and maintained in production—reliably and responsibly. You’ll work across product, data science, and engineering to lead delivery of complex ML systems. You’ll also define the core MLOps capabilities for the business and establish the standards and patterns that accelerate safe, scalable AI deployment across teams.
ML Systems Design & Delivery
• Lead the architecture and delivery of ML systems that power real-time and batch predictions at scale
• Design production pipelines for training, deployment, and monitoring using modern MLOps tooling
• Take ownership of technical quality, resilience, and observability of critical ML services
• Build reusable tools and frameworks to enable fast, safe experimentation and deployment
Platform, Standards & MLOps Foundations
• Define and build the core MLOps capabilities for the organisation, including training pipelines, deployment frameworks, and observability tooling
• Establish standardised patterns and best practices to accelerate model development, testing, and deployment
• Lead the evolution of our ML platform, working with engineering partners to improve scalability, governance, and developer experience
• Contribute to responsible ML practices—supporting auditability, explainability, and model health monitoring
Partner with data scientists to take models from prototype to production with clear interfaces and robust engineering
• Provide mentorship, pair programming, and code reviews for other engineers across the AI function
Stay ahead of developments in MLOps, LLM infrastructure, and AI engineering best practices
• Influence long-term strategic direction for ML tooling and delivery across the organisation
• Help build a high-performing, inclusive, and collaborative ML Engineering culture
Extensive experience designing and deploying ML systems in production
• Deep technical expertise in Python and modern ML tooling (e.g. MLflow, TFX, Airflow, Kubeflow, SageMaker, Vertex AI)
• Experience with infrastructure-as-code and CI/CD practices for ML (e.g. Strong understanding of ML system lifecycle: testing, monitoring, governance, observability
• A background in software engineering, computer science, or a quantitative field—or equivalent experience leading ML systems in production
You’ll have the tools and autonomy to drive your own career, supported by a team of amazingly talented people.
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!
#
Apply
Location:
London
Job Type:
FullTime

We found some similar jobs based on your search