Machine Learning Engineering Manager

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At Cleo, we are 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 is the future we are creating.

Cleo is a profitable, fast-growing unicorn with over $200 million in ARR and growing over 2× year-over-year. This is a chance to join a team of brilliant, driven individuals who are passionate about making a real difference. We seek individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact.

You will join the existing data science function here at Cleo; a thoughtful and collaborative team of ML engineers, analysts, and data engineers with significant industry experience. You will build and deploy production models that developers will feed directly into the product. This position is essential in the expansion of both product and business. We are highly data-driven, whether that be understanding natural language, deriving insights from financial data, or determining which financial product is best suited to a user.

You will be working on a hugely impactful workstream, focused on the machine learning that underpins our Chat feature. You will be shaping how Cleo uses LLMs to have more engaging, accurate, and personalised conversations about money.

What You’ll Be Doing:

• Understanding core problems faced by our Chat team and coordinating the ML function’s contribution to solving them.
• Finding opportunities for model and product improvements in Cleo's extensive datasets of customer behaviour.
• Responsible for people management of the ML engineers in your squads, coaching and developing them to deliver on the roadmap.
• Building out the headcount plan and responsible for all hiring and team development within your area to support our growth.

About You:

• Extensive experience building and deploying Machine Learning models to production.
• Experience managing and developing high performing teams of data scientists and ML engineers.
• 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 seeing business impact.
• Ability to write production quality Python code and a willingness to be somewhat hands-on.

Nice to haves:

• Domain knowledge of NLP, including evaluating LLM systems and fine-tuning LLMs or other transformer models.
• A strong ability to communicate findings to non-technical stakeholders in a concise and engaging manner.
• Experience with containers and container orchestration: Kubernetes, Docker, and/or Mesos.
• Experience using vector databases such as OpenSearch.

The recruitment process:

• Interview with a Recruiter (30 mins)
• Interview with the Hiring Manager (30 mins)
• Technical Interview (30 mins)
• White-boarding session (60 mins)
• Technical Discussion (45 mins)
• Management Skills Interview (30 mins)

What do you get for all your hard work?

A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles. Work at one of the fastest-growing tech startups, backed by top VC firms.