Lead Machine Learning Engineer (Credit Risk)
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 $200 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 Lead Machine Learning Engineer (Credit Risk) Machine Learning Engineers at Cleo work on building novel solutions to real-world problems. In this role the work will be centred around building and deploying machine learning models to power our credit risk engines. This is an exciting opportunity to help drive our models to be the best in the business; innovate on the future of credit modelling and have a real impact on the company bottom line whilst doing so! 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. 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
- Deployed some of the best in class credit decisioning models which affect millions of customers, whilst only using open banking data rather than traditional credit scoring
- Developed models to interpret transactional data, enhancing the understanding of users’ finances. Think about your bank statement—how often do you not recognise a transaction on first review?
- Created contextual intent classifiers to understand user conversations with Cleo, enabling tailored and accurate platform responses.
- Engineered ML models to identify and deliver relevant actions to users within Cleo, ensuring a seamless, context-aware conversational experience.
- Built models to evaluate risk in customer interactions with bank transaction features and user activities.
- Developed optimisation models to improve payment success rates for customers while minimising business costs, tackling this as a two-sided optimisation challenge.
- Designed and implemented AI agents to analyse and extract insights from users’ transactional data.
- Experience deploying multiple machine learning models into production; familiarity with Docker containers and container orchestration tools is a plus
- 5+ years of experience in data science, machine learning engineering, or related roles
- 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
- Strong ability to communicate findings to non-technical stakeholders
- Experience of leading projects involving multiple people including the development of a short term road map
- Comfortable breaking down work incrementally
- Line management experience would be a plus for this position
- Talent Screen with a Talent Partner (30 mins)
- Interview with the Hiring Manager (30 mins)
- Technical Interview (45 mins)
- White-boarding session (60 mins)
- Technical Discussion (45 mins)
- A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles. You can view our public progression framework and salary bandings here: (Please note that this a DS4 position)
- Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures
- A clear progression plan. We want you to keep growing. That means trying new things, leading others, challenging the status quo and owning your impact. Always with our complete support.
- Flexibility. We can’t fight for the world’s financial health if we’re not healthy ourselves. We work with everyone to make sure they have the balance they need to do their best work
- Work where you work best. We’re a globally distributed team. If you live in London we have a hybrid approach, we’d love you to spend one day a week or more in our beautiful office. If you’re outside of London, we’ll encourage you to spend a couple of days with us a few times per year. And we’ll cover your travel costs, naturally.
- Company-wide performance reviews every 6 months
- Generous pay increases for high-performing team members
- Equity top-ups for team members getting promoted
- 25 days annual leave a year + public holidays (+ an additional day for every year you spend at Cleo, up to 30 days)
- 6% employer-matched pension in the UK
- Private Medical Insurance via Vitality, dental cover, and life assurance
- Enhanced parental leave
- 1 month paid sabbatical after 4 years at Cleo
- Regular socials and activities, online and in-person
- We'll pay for your OpenAI subscription
- Online mental health support via Spill
- Workplace Nursery Scheme