Senior Machine Learning Engineer

About The Company

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 $300 million in ARR and growing over 2× 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.

Senior Machine Learning Engineers at Cleo work on building novel solutions to real‑world problems. This could involve creating chatbots that coach our users around their financial health, building classifiers to better understand transaction data, or optimizing transactions within our payments platform. Ultimately, we’re looking for a brilliant senior machine learning engineer to join us on our mission to fight for the world’s financial health.

You’ll lead technical work within a team of adaptable, creative, and product‑focused engineers, train and integrate cutting‑edge machine learning across a variety of products, and deploy them into production for millions of users.

• Training and fine‑tuning models to solve customer problems.
• Deploying these models into our production environments using our in‑house ML platform.
• Integrating with large‑language models hosted by OpenAI, Anthropic, GCP, AWS, and others.
• Working cross‑functionally with backend engineers, data analysts, UX writers, product managers, annotation teams, and others to ship features that improve our users’ financial health.
• Taking the initiative to propose and lead technical work toward problems that were previously unknown or poorly understood.
• Driving change at the chapter level that affects multiple squads.
• Mentoring and advising colleagues on model choice, architecture, and evaluation, and promoting best practices for how we use LLMs.
• Developed deeper understanding of users’ finances through models extracting meaning from transaction data.
• Developed contextual intent classifiers to understand conversations users have with Cleo.
• Built ML models to present user actions in a contextual way within conversations.
• Built ML models to assess risk of customers using bank transaction features and user activity.
• Built models to optimize payment success for our customers and optimize business costs.

• Excellent knowledge of both data science (Python, SQL) and production tools.
• Deep understanding of probability and statistics fundamentals.
• Big‑picture thinking to diagnose problems and operationalize research.
• Top‑tier communication skills to partner with product and commercial leaders.
• Industry‑leading contributions to your field communicated through conferences, blogs, talks, or open‑source projects.
• Advanced degree in a quantitative discipline or equivalent commercial experience.
• Nice to have:
  Strong experience with additional programming languages such as Java, Scala, or C++.

• Interview with a recruiter (30 minutes).
• Interview with the hiring manager (30 minutes).
• Python coding interview (45 minutes).
• White‑boarding session (60 minutes).
• Technical discussion (45 minutes).

Cleo