Mid-Senior Backend Engineer; ML integrations

Join to apply for the Mid-Senior Backend Engineer (ML integrations) role at Cleo

Join to apply for the Mid-Senior Backend Engineer (ML integrations) role at Cleo

About Cleo

At Cleo, we're not just building another fintech app. We're embarking on a mission to fundamentally change humanity's relationship with money. Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket. That's the future we're creating.

About Cleo

At Cleo, we're not just building another fintech app. We're embarking on a mission to fundamentally change humanity's relationship with money. Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket. That's the future we're creating.

Cleo is a rare success story: a profitable, fast-growing unicorn with over $200 million in ARR and growing over 2x year-over-year. This isn't just a job; it's a chance to join a team of brilliant, driven individuals who are passionate about making a real difference. We have an exceptionally high bar for talent, seeking individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact.

If you’re driven by complex challenges that push your expertise, the chance to shape something truly transformative, and the potential to share in Cleo’s success as we scale, while growing alongside a company that’s scaling fast, this might be your perfect fit.

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

About

The Role

You’ll join the team responsible for building and maintaining the decisioning systems that power Cleo’s core product. This is one of the most business-critical domains at Cleo and one of our most impactful - directly driving user experience, growth, and profitability.

Your primary focus will be integrating ML-driven credit and eligibility models into our Ruby on Rails monolith. These models, written in Python by ML engineers and data scientists, require robust, scalable integration patterns; you’ll own the productionisation of those services: from data ingestion and interface design to monitoring, alerting, and runtime observability.

You’ll work closely with ML engineers, analysts, and PMs to expose model outputs cleanly, help debug behavioral anomalies, and ensure that stakeholders have the tooling they need to understand how decisions are made.

You’ll also be part of our wider Ruby chapter, working across our Ruby monolith to improve it for both our users as well as your fellow engineers.

What We’re Looking For

You’re a backend engineer who’s comfortable working in technically complex domains - particularly those involving machine learning, financial decisioning, or large-scale data systems.

You're proficient in Ruby and have experience building and maintaining production systems that interface with machine learning models, data pipelines, or high-throughput decision engines. Exposure to Python and ML concepts is a plus, but deep ML knowledge isn’t required.

You care about observability, system reliability, and deployment best practices. You know how to make integrations robust and maintainable, and how to ensure they operate correctly in production over time.

You’re data-aware - able to reason about data lifecycle, ownership, transformations, and how downstream consumers rely on it. You’re also a strong cross-functional collaborator, able to work closely with product managers, analysts and ML engineers to debug issues and iterate quickly.

Our Tech Stack

Cleo is built as a Ruby on Rails monolith with a single React Native app frontend, utilising Type Script. We also leverage Python for machine learning services and Postgre

SQL for our database, all hosted on AWS. Our CI/CD pipeline is fully automated, with production deployments happening on every merge via Heroku. Our backend engineers deploy multiple times a week, and we release our frontend app to Google and Apple for review at least once a week.

While we take a pragmatic approach, we place a strong emphasis on quality. Our code is peer-reviewed, and we…