Senior Manager - Machine Learning Engineering

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 the Senior Manager for Machine Learning Engineering, you will lead, scale, and continuously mature a high-performing team delivering high quality machine learning solutions. Drive the long-term technical strategy, delivery excellence, and team development for ML engineering across the organisation. Working closely with Data Science, Product, Technical Capabilities, and wider Engineering leadership, ensure ML products and platforms are robust, secure, scalable, and aligned with strategic business outcomes. Lead by example in embedding engineering best practices, modern ML approaches, and a culture of innovation and technical excellence.

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 be doing:

• Lead, grow, and inspire a team of Machine Learning Engineers across multiple career levels, enabling high performance and strong team health through mentorship, coaching, and clear performance expectations.
• Shape and execute the technical strategy for ML engineering in collaboration with Data Leadership and Principal Engineers, focusing on scalable, automated, and maintainable systems.
• Champion and embed ML Ops best practices – including model lifecycle management, testing and validation, deployment (CI/CD) and serving, monitoring and observability.
• Collaborate with Tech Leadership to drive forward-looking architectural decisions, modernise infrastructure, and reduce technical debt, ensuring the ML platform is fit for long-term business use.
• Partner with Product Managers, Data Scientists, and Principal Engineers to translate business problems into machine learning products with measurable impact.
• Ensure teams operate with a strong sense of ownership, following “Build, Run, Own” principles, and maintain operational excellence in live services.
• Oversee delivery of complex cross-team ML initiatives, managing dependencies and risks, and aligning delivery with roadmaps and business timelines.
• Influence and guide engineering initiatives on technical standards, reusability, data security, and platform interoperability.
• Represent the ML Engineering function as part of the data and engineering leadership communities—contributing to organisational improvements in culture, capability, and technical maturity.

What we’d like to see from you:

Must Have

• Proven experience leading and managing high-impact engineering teams in ML, data, or platform domains.
• Strong technical background in ML engineering, including production deployment, monitoring, and scaling of models.
• Deep understanding of ML Ops practices, infrastructure automation, and the ML lifecycle in production environments.
• Solid experience with cloud-native architecture (AWS, GCP or Azure), containerisation (e.g. Docker, Kubernetes), and big data processing frameworks (e.g. Spark, BigQuery).
• Expertise in Python and SQL, with working knowledge of ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Demonstrated ability to lead through ambiguity and complexity, making pragmatic and scalable technical decisions.
• Excellent communication and stakeholder engagement skills, with the ability to influence across engineering and business boundaries.
• Passion for growing people and building diverse, inclusive teams.

Preferred

• Experience with modern ML platforms such as Databricks or Vertex AI.
• Exposure to deploying and optimising LLMs or other frontier models in production.
• Background in regulated environments or sectors with sensitive data governance needs.
• Track record of delivering horizontal platform capabilities or ML tools used across multiple teams.
• Active contributor to engineering culture, including mentoring, community-building, and technical leadership development.

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!