Machine Learning Engineering Manager - Growth Spain / remote

Machine Learning Engineering Manager - Growth Office: United Kingdom Remote: UK Apply for this role

About the company 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 $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 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.

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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 talented 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 (handling acquisition, channels, campaigns) and Growth Personalisation (handling 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 usersDrive 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 & personalization - 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. That context is gold.
• 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've open source 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 (GCP, AWS, etc.)
• Experience with typical ML stacks (scikit learn, XGBoost, TensorFlow/PyTorch, or similar)

Leadership Experience

• 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 - you know when to step in and when to empower
• Comfort navigating ambiguity and making decisions with incomplete information

Mindset & Values

• You genuinely care about impact - shipping models that drive real business outcomes, not just optimising metrics in isolation
• You're intellectually curious and humble - you don't have all the answers and you're excited to learn from your team
• 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 translate for stakeholders without over simplifying
• You have strong communication skills - you can explain complex ML concepts clearly, both to engineers and to non technical partners

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, Balderton & EQT Ventures
• 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'd love you to spend one day a week or more in our beautiful office. If you're outside of London . click apply for full job details