Machine Learning Engineering Manager - Personalisation
London, United Kingdom - Deliveroo · Full-time · Hybrid · Posted Oct 13, 2026
At a glance
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- London, United Kingdom - Deliveroo
About the role
- We’re looking for a Machine Learning Engineering Manager to join us in London on a hybrid basis (3 days a week).
- In this role, you’ll lead the team that owns intelligence across our ordering experience, from store page and item selection through cart, upsell and checkout, plus bundling.
- Personalisation is one of the biggest levers we have to drive value to our customers, and your team will make the app feel less like a generic catalogue and more like one that understands what each customer is trying to do.
Responsibilities
- Lead and develop a high-performing team of around 12 Machine Learning Engineers, distributed across multiple pods and spread across London, Finland and Berlin, fostering a culture of technical excellence, ownership and rapid experimentation.
- Own and evolve the ranking, recommendation and personalisation systems across ordering surfaces, helping customers find the right items quickly as our selection grows.
- Set the technical vision for the team’s ML ecosystem, balancing near-term product goals with longer-term bets on areas like on areas across recommendations to agentic approaches, and intent-aware experiences that adapt dynamically to how customers browse and act.
- Lead the unification of our recommendation models across brands (Deliveroo, Wolt and DoorDash) and markets, working out how to power personalisation at global scale while keeping it feeling hyperlocal, and how to balance reusable core models against surface-specific adaptations without ending up with a sprawl of models.
- Partner with Product, Data Science and neighbouring engineering teams to identify high-impact opportunities, define roadmaps and translate ambiguous business problems into ML solutions.
- Provide technical guidance on modelling approaches, ML system design and production architecture, stepping in to challenge modelling decisions where needed without becoming a bottleneck.
- Drive key marketplace metrics such as conversion and engagement, balancing velocity and scope against sustainable, long-term technical quality.
- Stay close to the code so you understand how your team actually works, and help evolve the AI-assisted engineering practices and tooling that empower the team.
Requirements
- Proven experience line-managing ML Engineers, ideally 6 or more direct reports, with a track record of building high-performing teams, coaching engineers through career progression and managing a horizontally distributed team across multiple pods or workstreams.
- Significant experience building and deploying machine learning systems in production at scale, in areas like Recommendations, Personalisation, Search, Ranking or Information Retrieval.
- Strong stakeholder management across product, engineering and business functions, with experience working across multiple teams and geographies.
- A pragmatic, impact-focused mindset, prioritising outcomes and customer experience over theoretical perfection.
Benefits
- Competitive salary
- Equity options
Workplace
- Hybrid basis (3 days a week)
Skills
- Machine Learning
- Recommendations
- Personalisation
- Search
- Ranking
- Information Retrieval
