Key Skills

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 an Tech Lead ML Manager to join the existing data science function at Cleo. You’ll be working on models that support our understanding of a user’s financial life, building our foundational capabilities upon which all our product innovation depends, from the chat based Financial Assistant to our credit products. You’ll take on technical leadership and ownership of a workstream within the Financial Understanding pillar. We work at the intersection of LLMs and classical machine learning, trying to bring the advanced capabilities that are now possible at the speed and scale necessary for the size of Cleo’s userbase. Leading and managing a team of circa. 4 MLE’s Deploying machine learning models into production Collaborating with product managers, backend engineers and analysts to play an active role in the planning and sequencing of work for the squad. Helping define the roadmap for the squad/workstream 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 Experience with both LLMs and classical machine learning Comfortable with complexity & developing a holistic understanding of a system in order to propose & build solutions 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, taking technical ownership of a workstream in the Financial Understanding pillar. Deploy machine learning models into production, collaborate with product managers, backend engineers, and analysts on planning and sequencing work, and help define the squad's roadmap.

Requirements

Candidates need at least five years of experience in data science, machine learning engineering, or a related role, including at least one year of management experience. They should be able to write production-quality Python, have experience deploying machine learning models, understand both large language models and classical machine learning, and be comfortable solving complex system-level problems.

Benefits

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