Machine Learning Engineering Manager, Financial Assistant

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 ML Engineering Manager to join the existing data science function at Cleo - a collaborative team of ML engineers, analysts, and data engineers - to build and deploy production models that go directly into the product. You'll lead the ML workstream behind our Financial Assistant feature, shaping how Cleo uses LLMs to have more engaging, accurate, and personalised conversations about money.

This is a people management role: you'll manage the ML engineers across your squads, own the headcount plan, and be responsible for hiring and team development in your area.

• Understand the core problems faced by the Financial Assistant team and coordinate the ML function's contribution to solving them

• Find opportunities for model and product improvements in Cleo's extensive customer behaviour datasets

• Manage the ML engineers in your squads - coaching and developing them to deliver on the roadmap

• Build out the headcount plan and own hiring and team development within your area to support growth

What we're looking for 🕵️

• Extensive experience building and deploying machine learning models to production

• Experience managing and developing high-performing teams of data scientists and ML engineers

• A habit of keeping abreast of the latest research and experimenting productively with new technologies, including LLMs and LLM agent design

• Experience owning an ML roadmap, driving new ideas through to business impact

• Ability to write production-quality Python code, with a willingness to stay somewhat hands-on

• Nice to have: domain knowledge of NLP, including evaluating LLM systems and fine-tuning LLMs or other transformer models

• Nice to have: a strong ability to communicate findings to non-technical stakeholders concisely and engagingly

• Nice to have: experience with containers and container orchestration - Kubernetes, Docker, and/or Mesos

• Nice to have: experience using vector databases such as OpenSearch

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 👈