Staff Machine Learning Engineer

Compare the Market; London; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

A leading company is seeking a Staff Machine Learning Engineer to design and scale their ML infrastructure. This role includes overseeing ML system delivery and establishing operational standards while fostering an inclusive culture. Join a forward-thinking team to drive impactful AI solutions while enjoying generous benefits and a supportive work environment.

Benefits

Generous holiday allowance

Private healthcare

Electric car scheme

Paid development and wellbeing days

Qualifications

• Extensive experience in ML systems design & deployment.
• Deep expertise in Python and ML tooling.
• Proven ability to build reusable ML pipelines.

Responsibilities

• Lead architecture and delivery of ML systems for predictions.
• Define and build MLOps capabilities for the organization.
• Mentor engineers and influence ML tooling direction.

Skills

Python

MLOps

Collaboration

Communication

Monitoring

Education

Degree in Computer Science, Software Engineering, or related field

Tools

MLflow

Airflow

Kubeflow

Terraform

Job description

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!
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.

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:
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

What we’d like to see from you:
• 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

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!

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