Lead Machine Learning Engineer - Payments

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.

If there’s anything we can do to accommodate your specific situation, please let us know.

About Cleo

Most people come to Cleo to do work that matters. Every day, we empower people to build a life beyond their next paycheck, building a beloved AI that enables you to forge your own path toward financial well-being.

Backed by some of the most well-known investors in tech, we’ve reached millions of people to support them throughout their financial lives, from their first paycheck to their first home and beyond. We're hitting headlines too. This year, Forbes named us as one of their Next Billion Dollar Startups, and we were crowned the 'Hottest Tech Scaleup' at the Europas.

Follow us on LinkedIn to keep up to date with new product features and insights from the team.

The team 

You’ll join the existing Data Science function here at Cleo; a thoughtful and collaborative chapter of 20+ dedicated data scientists & ML engineers, with significant industry experience that is at the heart of everything we do at Cleo. You’ll build and deploy production models that developers will feed directly into the product.

This position is essential in the expansion of both product and business. We are highly data driven, whether that be understanding patterns in users’ cashflow, scoring credit risk, or determining which of Cleo’s features is best suited to a user. We have interesting problems to solve on an ever-increasing scale.

You'll take ownership of the intelligent optimisation of payments, a significant workstream that has a direct impact on the company's financial performance. Your role will involve collaborating closely with others in your cross-functional team to investigate and comprehend business issues. You will use your analytical abilities to generate potential solutions and employ machine learning techniques to enhance processes. In the longer term, the role could incorporate other ML applications such as fraud detection and credit risk.  

What you’ll be doing

• Improving our current machine learning models and deploying into production
• Actively building and productionising classifiers - no dependencies on engineering teams
• Collaborating with various departments within the organisation, including product, operations, and commercial, to leverage machine learning and analytics in order to uncover opportunities for optimization
• Carrying out deep analysis into the core aspects of how Cleo runs to be able to fully understand the levers and propose opportunities to improve
• Working closely with engineers to make sure we collect the right data to produce relevant business insights

About you

• At least 4 years of experience in data science, ML engineering or related roles
• Ability to write production quality code in Python and SQL
• Experience deploying machine learning models into production
• Track record in payments, pricing, or other business process optimisation problems
• Comfortable with complexity & developing a holistic understanding of a system in order to propose & build solutions
• A strong ability to communicate findings to non-technical stakeholders in a concise and engaging manner

Nice to have

• Experience with the US payments ecosystem
• Experience with containers and container orchestration: Kubernetes, Docker, and/or Mesos, including lifecycle management of containers

What do you get for all your hard work?

• Salary bandings are open source. You'll also receive a generous equity package. You can view our progression framework and salary bandings here: https://cleo-ai.progressionapp.com/teams/data-hytlm2bwmux2. This role will be at DS4+ banding salary depending on experience.
• Work at one of the fastest-growing tech startups, backed by top VC firms like Sofina, 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 treat you as humans first, employees second. Because we can’t fight for the world’s financial health, if we’re not healthy ourselves. This means all the usual perks but it also means flexibility. We take pride in being a flexible workplace that trusts our Cleople to deliver their best work, giving you the autonomy to structure your day around morning drop-offs to school or daily dog walks.
• Hybrid-first: Join our hybrid-first team, where we blend the best of both remote and in-office work. If based in London, we'd love to see you 1-2 times a week. On Wednesdays, we buy you lunch but you can come to the office on whichever days work best for you!
• Other benefits;
  • 25 days annual leave a year + public holidays (+ an additional day for every year you spend at Cleo)
  • Check out our new benefits package here: https://web.meetcleo.com/blog/big-benefits-energy-the-latest-cleo-employee-benefits
  • 6% employer-matched pension in the UK
  • Company-wide performance reviews every 8 months e.g every 2 terms, in line with our termly cycles (Jan-April, May-Aug, Sept-Dec):
    • Generous pay increases for high-performers and high-growth team members
    • Equity top-ups for team members getting promoted
  • 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
  • And many more!

UK App access: The Cleo app is no longer downloadable in the UK (but only until next year). If you’re an existing user, you’ll still have access to the app. But some features won’t be available (just for a little while). Why? 99% of our users are based in the US – where financial health is often overlooked. We’ve decided to shift our focus to where we can provide the most value and make the greatest impact for users who need it most. Then we’ll be able to apply what we learn to better support our UK users in the future. Check out this page for more information.