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Tech Lead Machine Learning Manager - Payments

Cleo

Full-time
5-10 years experience
On-site

Key Skills

Machine Learning
Machine Learning Engineering
Team Management
Production-Quality Python
Production Model Deployment
Payments Optimization
Credit Collections
Subscription Retention
Payments Recommendation Systems
Classification Models
Tabular Data
Risk Decisioning
Pricing
Business Process Optimization
Cross-Functional Collaboration
Stakeholder Communication

Job Description

Most money apps talk at you. Cleo talks back ✨ We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process 💰 For everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money. We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in. Follow us on LinkedIn for new features and the occasional roast 🔥 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 👈 What Matters Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits. We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know. We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Core Responsibilities

Lead and manage a team of approximately four machine learning engineers responsible for optimizing payment systems across credit collections and subscription retention. Partner with product, engineering, and analytics teams to identify business problems, deploy production machine learning models, and ensure the right data is collected for future models.

Requirements

Candidates need at least five years of experience in data science, machine learning engineering, or a related field, including at least one year of management experience. They must be able to write production-quality Python, deploy machine learning models, demonstrate experience in payments or related business optimization problems, and communicate findings clearly to non-technical stakeholders.

Benefits

  • Equity
  • Health Insurance
  • Mental Health Support
  • Paid Sabbatical
  • Learning And Development Platform
  • Pension Or Retirement Contributions
  • Location-Specific Leave Entitlements

About Cleo

Industry: Financial Services

Company size: 201-500 employees

Cleo was founded in 2016 by people who'd been burned by banks and frustrated by a financial system that wasn't built for the people using it. We created Cleo to change the world's relationship with money. More than a budgeting app, Cleo is an AI financial assistant that helps millions of people understand their money, build healthier financial habits, and make smarter decisions through personalized conversations, insights, and tools. We believe managing money should feel simple, empowering, and even enjoyable, not confusing or intimidating. Since launching, we've grown from a small team with a big idea into a company of more than 250 people, raising an $80 million Series C led by Sofina and reaching a $500 million valuation. Today, we're redefining what personal finance looks like in the age of AI by building products that millions rely on every day. We're just getting started.

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