Machine Learning Engineering Manager - Growth

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. We're creating that future. Cleo is a profitable, fast-growing unicorn with over $300 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 transformative, and the potential to share in Cleo's success as we scale, while growing alongside a fast-moving company, this might be your perfect fit.

About The Role
We're looking for an exceptional ML Engineering Manager to lead the Machine Learning efforts across our Growth team — the squad responsible for making smart, personalised decisions about what each of our 4M+ users sees, when they see it, and how we optimise for long-term value. You'll manage a team of ML Engineers and collaborate with Marketing Engineers, Product Designers, PMs, and Data Scientists to build the systems that drive revenue growth while maximising lifetime value (LTV) for every single user. This is a high-impact role where you'll directly influence how we grow, retain, and monetise our user base.

The Growth team spans two squads: Growth Marketing (acquisition, channels, campaigns) and Growth Personalisation (on-app prompts, offers, and recommendations). Together, we maximise revenue while protecting long-term health.

What We're Building
ML-powered prompt recommender systems that decide which offer or action to show each user.
Personalised messaging and incentive systems based on user context and history.
Incrementality testing to measure true causal lift from our interventions.
Multi-armed bandits and online learning to optimise in near real-time.
Scoring and ranking systems that balance short-term revenue with long-term retention.

What You'll Be Doing
Lead ML Strategy & Delivery
Own the ML roadmap for Growth, working with the PM and leadership to prioritise high-impact projects.
Lead the design and delivery of systems that personalise prompts, offers, and messaging to individual users.
Drive continuous improvement across ML models, from concept to experiment to production.

Build & Mentor Your Team
Recruit, onboard, and develop 3-5 ML Engineers (mix of IC and growing managers).
Create a high-performing culture where people want to do their best work.
Balance mentorship with accountability - push the team to ship quality work quickly.
Support career growth and technical development; create clear pathways for levelling up.

Collaborate at Scale
Work closely with Growth Marketing Engineering on infrastructure, experimentation, and deployment.
Partner with Product on feature prioritisation and user experience design.
Engage Analytics on metrics, instrumentation, and incrementality testing.
Communicate ML impact clearly to leadership and across the business.

Own Technical Excellence
Review ML designs and code; ensure quality without becoming a bottleneck.
Guide architectural decisions on model serving, latency, scalability.
Maintain (and improve) the team's ML infrastructure and tooling.
Lead incident response when models or systems degrade in production.

Drive Experimentation & Learning
Champion a test-driven approach to ML - we measure impact, not just accuracy.
Ensure robust experiment design, holdout groups, and statistical rigor.
Build a learning culture where failures are dissected and shared.
Publish learnings - both internally (to other teams) and externally.

About You
You're a strong technical leader with hands-on ML experience, particularly in areas like:
Recommender systems & personalisation - ranking models, candidate generation, multi-armed bandits, contextual decision-making.
Uplift modelling & incrementality testing - understanding causal impact and incremental lift.
Ad targeting & auction systems - optimising bidding, audience selection, and campaign performance.
Marketing mix modelling (MMM) - attribution, channel contribution, budget allocation.

You've shipped ML products at scale, managed teams (ideally 3-5 engineers), and you understand the balance between rigorous experimentation and speed to market. You care deeply about bringing good vibes while pushing the team to make it happen, and you're genuinely excited by the technical challenges in personalisation and growth.

What Makes You a Good Fit
Technical depth: You can code, debug, and review ML systems. You're not a pure manager, you're in the trenches with your team on high-impact projects.
Growth mindset: You learn at speed, adapt quickly, and aren't afraid to challenge assumptions with data. You see every project as a chance to level up the team's capabilities.
No bullshit: You're direct, honest, and pragmatic. You say what you mean and you mean what you say.
Cross-functional leadership: You can translate between ML complexity and business impact. You collaborate naturally with PMs, Data Engineers, and Analytics - no silos.
User-centric: You obsess over impact - not just model accuracy, but real-world outcomes like retention, revenue, and lifetime value.

What We're genuinely excited about
You've built recommender or ranking systems at scale - Spotify playlists, Netflix recommendations, Amazon product ranking, Pinterest pins, TikTok feed, Twitter/X timeline.
You've done causal inference work - incrementality testing, uplift modelling, experimentation design. You understand the difference between correlation and causation.
You've managed through hypergrowth - you've scaled a team, navigated process changes, and kept quality high while shipping at velocity.
You have growth or marketing domain experience - you understand LTV, CAC, channel economics, attribution, and retention. You speak fluent 'growth'.
You're open-sourced or published ML work - papers, blog posts, talks. You like to share knowledge.

What We're Looking For
Technical Experience
5+ years in ML/Data Science roles, with at least 2+ years in a leadership or senior technical IC capacity.
Hands-on experience shipping ML products end-to-end (not just notebooks) - ideally in personalisation, recommender systems, or growth.
Strong fundamentals in statistical inference, experimental design, and causal reasoning.
Production ML experience: model serving, latency optimisation, A/B testing, monitoring.
Comfortable with Python, SQL, and cloud platforms.
Experience with typical ML stacks (scikit-learn, XGBoost, TensorFlow/PyTorch, or similar).

Track record of building and scaling high-performing teams.
Comfortable hiring, onboarding, and developing engineers from L2 to L4+.
Experience giving technical feedback, code reviews, and architectural guidance.
Ability to balance autonomy with accountability.
Comfort navigating ambiguity and making decisions with incomplete information.
You genuinely care about impact - shipping models that drive real business outcomes.
You're intellectually curious and humble.
You're a teacher and a learner - you enjoy helping others grow while continuing to develop your own skills.
You can operate effectively across technical and non-technical contexts.
You have strong communication skills - you can explain complex ML concepts clearly.

The recruitment process
Interview with a Recruiter (30 mins).
Interview with the Hiring Manager (30 mins).
Python Programming Interview (45 mins).
Whiteboard Interview (60 mins).
Management Skills Interview (60 mins).

What do you get for all your hard work?
A competitive compensation package (base + equity) with 3-yearly reviews, aligned to our termly OKR planning cycles.
The salary bandings for this position are: £150,000 - 170,000 London, Hybrid / £140,000 - 160,000 UK, Remote.
Work at one of the fastest-growing tech startups, backed by top VC firms.
A clear progression plan. We want you to keep growing. That means trying new things, leading others, challenging the status quo and owning your impact. Always with our complete support.
Flexibility. We can't fight for the world's financial health if we're not healthy ourselves. We work with everyone to make sure they have the balance they need to do their best work.
Work where you work best. We're a globally distributed team. If you live in London we have a hybrid approach, we encourage you to spend one day a week or more in our office. If you're outside of London, we'll encourage you to spend a couple of days with us a few times per year. And we'll cover your travel costs.
Company-wide performance reviews every 4 months.
Generous pay increases for high-performing team members.
Equity top-ups for team members getting promoted.
6% employer-matched pension in the UK.
25 days annual leave a year + public holidays.
1 month paid sabbatical after 4 years at Cleo.
We'll pay for your OpenAI subscription.
Private Medical Insurance via Vitality, dental cover, and life assurance.
Online mental health support via Spill.
Enhanced parental leave.
Workplace Nursery Scheme.
Regular socials and activities, online and in-person.

We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.