Lead Machine Learning Scientist, Customer Operations

About our Machine Learning Operations team:

The challenges are significant: we aim to transform customer service by reducing the time and effort required to resolve issues, enhancing customer confidence and satisfaction. As part of Operations, you’ll be at the forefront of our mission to provide unparalleled customer support experiences.

Your role will be pivotal in leveraging state-of-the-art machine learning techniques (including LLMs and autonomous agents) to understand customer problems. You will lead the development of an effective human-in-the-loop system that augments automation with the efforts of our support workforce (who we call COps). This allows us to more expediently and efficiently predict, identify, disambiguate, and route customer problems at scale to support a rapidly expanding company with global ambitions across multiple geographies.

You’ll be working closely with a team of ML engineers in Operations, embedded in product squads alongside data scientists, backend, mobile and web engineers, product managers, user researchers, designers, and operations specialists.

Your day-to-day:

As a technical individual contributor, you’ll be providing technical leadership and shipping highly impactful ML-based solutions. You’ll be embedded in a cross-functional product squad, working closely with product managers, data scientists, backend engineers, and designers in an agile environment. You’ll also be a technical leader within the wider Machine Learning discipline, helping to steer technical work and drive up standards.

This will involve:

• Working with stakeholders across the organisation to identify and scope out the most impactful opportunities to transform Customer Operations with Machine Learning.
• Leading the design and development of advanced Machine Learning models, exploring how LLMs, RAG, and sequence-based architectures can drive improvements in query resolution and routing.
• Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others.
• Steering ongoing technical strategy, working closely with our MLOps team and backend engineers to enable rapid iteration of models and optimisations of the full ML model lifecycle.

You should apply if:

What we’re doing here at Monzo excites you!

• You have a multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company
• You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact
• You're impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production
• You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
• You have extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices
• you’re comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity
• you want to be involved in building a product that you (and the people you know) use every day
• you have a product mindset: you care about customer outcomes and you want to make data-informed decisions
• You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain
• You’re adaptable, curious and enjoy learning new technologies and ideas

Nice to haves:

• Experience working with customer operations, capacity planning, forecasting, or in regulated institutions.
• Commercial experience writing critical production code and working with microservices.

The interview process:

Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions!

• 30 minute recruiter call
• 45 minute call with hiring manager
• 60 minute ML Modelling interview
• 60 minute Product & ML interview
• 60 minute behavioural interview

Our average process takes around 3-4 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on

What’s in it for you:

➕And much more, see our full list of benefits here

If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance

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