Staff Machine Learning Engineer

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 at pace. Every 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.

We'd love you to be part of our journey:

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. This is a high-impact, hands-on leadership role. 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.

Some of the great things you'll do:

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.

Technical Leadership & Collaboration

• Partner with data scientists to take models from prototype to production with clear interfaces and robust engineering
• Lead cross-team technical design sessions and architectural reviews
• Provide mentorship, pair programming, and code reviews for other engineers across the AI function

Innovation & Culture

• 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

Do you have experience in Terraform?, Do you have a Master's degree?, * 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. Terraform, GitHub Actions, ArgoCD)
• Proven ability to build reusable tooling, scalable services, and resilient pipelines for real-time and batch inference
• Strong understanding of ML system lifecycle: testing, monitoring, governance, observability
• Excellent collaboration and communication skills; able to influence cross-functional teams and lead complex technical work
• A background in software engineering, computer science, or a quantitative field-or equivalent experience leading ML systems in production