At a Glance
- Tasks: Lead ML strategies to personalise user experiences and drive revenue growth.
- Company: Join Cleo, a fast-growing fintech unicorn on a mission to transform financial relationships.
- Benefits: Competitive salary, equity options, flexible work, and generous leave policies.
- Other info: Exciting career growth opportunities and a supportive, inclusive culture.
- Why this job: Make a real impact in a dynamic environment while shaping the future of finance.
- Qualifications: 5+ years in ML roles with leadership experience; strong technical and collaborative skills.
The predicted salary is between 150000 - 170000 £ per year.
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've 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
- Well 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
- And many more!
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.
By submitting this application, I confirm that all the information given by me in this application for employment is true to the best of my knowledge and that I have not wilfully suppressed any material fact. I accept that if any information given by me in this application is false, my application may be rejected or employment may be terminated. By submitting this application, I agree that my personal data will be processed in accordance with Cleo AI's Candidate Privacy Notice.
Machine Learning Engineering Manager - Growth in London employer: cleo
Cleo is an exceptional employer that champions innovation and personal growth within a dynamic work culture. With a commitment to employee development, competitive compensation, and a flexible hybrid working model in London, Cleo fosters an environment where talented individuals can thrive while making a meaningful impact on the future of finance. Join a passionate team dedicated to transforming how people engage with their finances, all while enjoying generous benefits and opportunities for career advancement.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineering Manager - Growth in London
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn, especially those at Cleo. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Prepare for your interviews by diving deep into Cleo's mission and values. Show us how your skills align with our goal of transforming financial relationships. We love candidates who are genuinely excited about what we do!
✨Tip Number 3
Practice your technical skills! Brush up on your Python and ML concepts, as you might face some coding challenges. We want to see you shine in those areas during the interview process.
✨Tip Number 4
Don’t forget to showcase your past projects! Whether it’s a recommender system or an ML model, share your experiences and how they’ve prepared you for this role. We’re all about real-world impact!
We think you need these skills to ace Machine Learning Engineering Manager - Growth in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Machine Learning Engineering Manager role. Highlight your relevant experience in ML, especially in personalisation and growth, and show us how you can contribute to Cleo's mission.
Showcase Your Technical Skills:Don’t hold back on your technical prowess! Include specific examples of ML products you've shipped, particularly those that demonstrate your hands-on experience with recommender systems and causal inference. We want to see your coding skills shine!
Emphasise Collaboration:Cleo values teamwork, so highlight your experience working cross-functionally. Share examples of how you've collaborated with PMs, Data Engineers, and other teams to drive impactful projects. We love a good team player!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you're keen on joining our awesome team!
How to prepare for a job interview at cleo
✨Know Your ML Stuff
Make sure you brush up on your machine learning fundamentals, especially around recommender systems and causal inference. Be ready to discuss your hands-on experience with ML products and how you've tackled complex challenges in the past.
✨Show Your Leadership Skills
Cleo is looking for someone who can lead a team effectively. Prepare examples of how you've mentored engineers, fostered a high-performing culture, and balanced accountability with support. Highlight your experience in scaling teams during hypergrowth.
✨Communicate Clearly
You’ll need to translate complex ML concepts into business impact. Practice explaining your past projects in simple terms, focusing on outcomes like user retention and revenue growth. This will show that you understand both the technical and business sides of the role.
✨Embrace a Growth Mindset
Cleo values adaptability and continuous learning. Be prepared to discuss how you've learned from failures and adapted your strategies. Share specific instances where you challenged assumptions with data and how that led to better outcomes.