Tech Lead Machine Learning Manager - Payments

Meet the team 👥

Here at Cleo, we have ~45 ML engineers ✨ They are the builders behind the AI that powers our product. They design experiments, create models that personalise financial insights, deploy fraud detection systems and scale our conversational AI, making sure that what we build genuinely helps people feel better about their money. From shaping product features and building the models that personalise our users' money journeys, to tackling fraud, scaling our systems and giving leaders the insights they need, our data team is at the heart of it all.

About the role ✍️

We're hiring a Machine Learning Tech Lead to take on technical leadership and ownership of the Payments Intelligence team, managing a team of circa 4 MLEs. This team is responsible for optimising Cleo's payments systems - covering both credit collections and subscription retention - a workstream with a direct impact on the company's financial performance. You'll work closely with your cross-functional squad to understand business issues, then use your ML engineering skills to deploy best-in-class models that move the bottom line.

• Lead and manage a team of 4 MLEs

• Deploy machine learning models into production - classifiers, payments recommendation systems, and any other model that can have impact, typically working with tabular data rather than language models

• Collaborate with product managers, backend engineers, and analysts, playing an active role in planning and sequencing work for the squad

• Work closely with engineers to make sure the right data is collected to build future machine learning models

What we're looking for 🕵

• At least 5 years of experience in data science, ML engineering, or related roles

• At least 1 year of management experience, ideally of a small team

• Ability to write production-quality Python code

• Experience deploying machine learning models into production

• Track record in payments, pricing, risk decisioning, or other business process optimisation problems

• Comfortable with complexity, and developing a holistic understanding of a system in order to propose and build solutions

• A strong ability to communicate findings to non-technical stakeholders in a concise and engaging manner

• Nice to have: experience with credit collections

What we offer

We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements.

For the full breakdown on what's available in your location, visit our Candidate Hub 👈