Machine Learning Engineer - Personalisation London (London)

At Cleo, we are 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. Cleo is a profitable, fast-growing unicorn with over $200 million in ARR and growing over 2x year-over-year.

Machine Learning Engineers at Cleo work on building novel solutions to real-world problems, such as creating chatbots to coach our users around their financial health, creating classifiers to better understand transaction data, or optimising transactions within our payments platform.

Ultimately, we are looking for a brilliant Machine Learning Engineer to join us on our mission to fight for the world's financial health. You will be leading technical work within a team of adaptable, creative and product-focused engineers, who train and integrate cutting-edge machine learning across a variety of products and deploy them into production for millions of users.

What you’ll be doing:

• Training and fine-tuning models to help customers get more value from our chatbot and app through deeper personalisation.
• Integrating LLMs hosted by OpenAI, Anthropic, GCP, AWS.
• Working cross-functionally with backend engineers, data analysts, UX writers, product managers, and others to ship features that improve our users’ financial health.
• Driving the adoption of appropriate state-of-the-art techniques for recommendation, message campaign optimisation, and contextual bandits.
• Communicating the team’s successes and learnings at the company level and beyond.
• Developing a holistic view of personalisation and user-level features across Cleo.
• Supporting ML Engineers around problem framing, ML modelling, and evaluation.

Here are some examples of the kinds of product feature work our ML Engineers have taken part in over the last year:

• Designed and implemented AI agents to analyse and extract insights from users’ transactional data.
• Developed models to interpret transactional data, enhancing the understanding of users’ finances.
• Created contextual intent classifiers to understand user conversations with Cleo.
• Engineered ML models to identify and deliver relevant actions to users within Cleo.
• Built models to evaluate risk in customer interactions with bank transaction features.
• Developed optimisation models to improve payment success rates for customers.

What you’ll need:

• 3-5 years of experience in data science, machine learning engineering, or related roles.
• Excellent knowledge of both Data Science (Python, SQL) and production tools.
• Strong ability to communicate findings to non-technical stakeholders.
• Experience deploying machine learning models into production; familiarity with Docker containers and container orchestration tools is a plus.

Nice to have:

• Experience with recommender systems, personalisation, or ad optimisation.

What do you get for all your hard work?

• A competitive compensation package (base + equity) with bi-annual reviews.
• Work at one of the fastest-growing tech startups, backed by top VC firms.
• A clear progression plan.
• Flexibility in work arrangements.
• Other benefits include performance reviews, generous pay increases, annual leave, pension contributions, private medical insurance, enhanced parental leave, and more.

We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.