Overview
Machine Learning Engineer role at Cleo.
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.
About the Role
Machine Learning Engineers at Cleo work on building novel solutions to real-world problems. This can include creating chatbots to coach users around their financial health, building classifiers to better understand transaction data, or optimizing transactions within our payments platform. You will lead technical work within a team of adaptable, creative, product-focused engineers who train and integrate cutting-edge machine learning across products and deploy them into production for millions of users.
Responsibilities
- 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, enabling tailored 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.
What You’ll Need
- Excellent knowledge of Data Science (Python, SQL) and production tooling
- Experience building chat products
- A strong understanding of probability and statistics fundamentals
- Big-picture thinking to diagnose problems and productionise research
- Top-tier communication skills to partner with Product and Commercial Leaders
- Industry-leading contributions to your field (conferences, blogs, talks, or open-source projects)
- 3+ years of experience in data science, machine learning engineering, or related roles
- Ability to communicate findings to non-technical stakeholders
- Experience deploying machine learning models into production; familiarity with Docker containers and container orchestration is a plus
Recruitment Process
- Interview with a Recruiter (30 mins)
- Interview with the Hiring Manager (30 mins)
- Technical Interview (45-60 mins)
- White-boarding session (60 mins)
- Technical Discussion (60 mins)
What you get
- Competitive compensation package (base + equity) with bi-annual reviews, aligned to quarterly OKR planning. See our progression framework and salary bands here: https://cleo-ai.progressionapp.com/
- Work at a fast-growing tech startup backed by top VC firms Balderton & EQT Ventures
- Clear progression plan and support for growth
- Flexible working arrangements
- Global distributed team; London hybrid option with one day per week in the office; travel costs covered if outside London
- Company-wide performance reviews every 6 months
- Generous pay raises for high-performing team members
- Equity top-ups for team members getting promoted
- 25 days annual leave + public holidays, plus +1 day per year at Cleo up to 30
- 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
- OpenAI subscription paid by Cleo
- Online mental health support via Spill
- Workplace Nursery Scheme
- 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.
App access for people in the UK & Europe: If you are an iOS user, sign up to our TestFlight version of the app to explore functionality and features: https://testflight.apple.com/join/fDG9hWng
Job Details
- Seniority level: Mid-Senior level
- Employment type: Full-time
- Job function: Engineering and Information Technology
London, United Kingdom
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