(Senior) Machine Learning Engineer

Overview

About The Company About Cleo At Cleo, we’re not just building another fintech app. We’re embarking on a mission to fundamentally change humanity’s relationship with money. Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket. That’s the future we’re creating.

Cleo is a rare success story: a profitable, fast-growing unicorn with over $300 million in ARR and growing over 2x year-over-year. This isn’t just a job; it’s a chance to join a team of brilliant, driven individuals who are passionate about making a real difference. We have an exceptionally high bar for talent, seeking individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact.

If you’re driven by complex challenges that push your expertise, the chance to shape something truly transformative, and the potential to share in Cleo’s success as we scale, while growing alongside a company that’s scaling fast, this might be your perfect fit. Follow us on LinkedIn to keep up to date with new product features and insights from the team.

About The Role (Senior) Machine Learning Engineers at Cleo work on building novel solutions to real-world problems.

This really does vary but could be: creating chatbots to coach our users around their financial health, creating classifiers to better understand transaction data or even optimising transactions within our payments platform. Ultimately, we’re looking for a brilliant (Senior) Machine Learning Engineer to join us on our mission to fight for the world’s financial health. You’ll be leading technical work within a team of adaptable, creative and product-focused engineers, who train & integrate cutting edge machine learning across a variety of products and deploy them into production for millions of users.

We understand our customers, we understand their pain, and we are passionate about helping them. Check out this blog on Isabelle’s journey in ML at Cleo. What You’ll Be Doing Training and fine-tuning models to solve customer problems.

Deploying these models into our production environments using our in-house ML platform, which you can read about on our blog: Let’s have an Espresso: MLOps at Cleo. Or integrate with LLMs hosted by OpenAI, Anthropic, GCP, AWS and others.

Working cross-functionally with backend engineers, data analysts, UX writers, product managers, annotation teams, and others to ship features that improve our users’ financial health.

Taking the initiative to propose & lead technical work towards problems that were previously unknown or poorly understood. Driving change at the chapter level that affects multiple squads.

Mentoring & advising colleagues on their choices of models, architecture, and evaluation, promoting best practices for how we use LLMs.

Here Are Some
Examples, Big And Small, Of The Kinds Of Product Feature Work Our ML Engineers Have Taken Part In Over The Last Year Developed deeper understanding of users finances through models extracting meaning from transactional data. Think about your bank statement, how often do you not know what a transaction is?

Developed contextual intent classifiers to understand what conversations users are having with Cleo, enabling control of how Cleo should respond

Building ML models to understand the actions that users have available to them in Cleo and provide those contextually in conversations

Built ML models to understand the risk of customers using bank transaction features and user activity

Built models to optimise the payment success for our customers and optimising the costs for the business. Think of this as a two-sided optimisation problem. Whatever problem you tackle, and whichever team you join, your work will directly impact those most in need, helping to improve their financial health.

What You’ll Need Excellent knowledge of both Data Science (python, SQL) and production tools A deep understanding of probability and statistics fundamentals

Big picture thinking to correctly diagnose problems and productionising research

Top tier communication skills, to be able to partner with Product and Commercial Leaders

Industry-leading contributions to your field, communicated through conferences, blogs, talks, or open-source projects

Advanced Degree in a quantitative discipline or equivalent commercial experience Nice to have Strong experience with additional programming languages, such as Java, Scala, C++

Industry-leading contributions to your field, communicated through conferences, blogs, talks, or open-source projects The recruitment process Interview with a Recruiter (30 mins)

Interview with the Hiring Manager (30 mins)

Python Coding Interview (45 mins)

White-boarding session (60 mins)

Technical Discussion (45 mins) What d

Company:

Cleo

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Classification, Industry, Machine Learning, NLP, United Kingdom