Senior Machine Learning Engineer

Deliveroo
London - The River Building HQPosted 10 April 2026

Job Description

Senior Machine Learning Engineer SENIOR MACHINE LEARNING ENGINEER Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale. We’re looking for several Senior Machine Learning Engineers to join our London teams. WHAT YOU’LL BE DOING In this role, you’ll help us develop the algorithmic and machine-learning systems that power Deliveroo, making automated decisions at massive scale across our three-sided marketplace. Based on the team you join, here's what your role may look like: 1. Ads – building and productionising ranking and bidding models that decide which sponsored content to show, balancing advertiser outcomes with a high-quality user experience. 2. New Verticals – developing recommendation and catalogue-quality models that help customers discover the right grocery and retail items while supporting growth and efficiency. 3. Consumer – improving modern recommendation, ranking and search systems that shape how customers discover and choose what to order, driving engagement and long-term growth. 4. Care – building ML and LLM-powered systems that support customer care operations, from understanding intent and sentiment to suggesting fair and consistent resolutions. 5. Merchants – owning and evolving core ML models that support our merchant ecosystem (for example around classification, matching and lead-scoring), and building new models and AI agents that help partners grow their business. Irrespective of the team, you will: - Design and build sophisticated machine learning models to solve fuzzy business problems - Productionise end-to-end ML solutions, moving from initial concept to shipping code that drives measurable impact on our global marketplace. - Collaborate in cross-functional squads alongside software engineers, data scientists, and product managers to build intelligent decision-making machines. - Mentor junior colleagues and contribute to our robust technical review process to maintain high engineering standards. WHAT YOU’LL NEED TO THRIVE Our ideal candidate will bring strong expertise in some of these areas and curiosity to grow in others: - Significant experience applying algorithmic solutions to complex business problems at scale. - Deep understanding of machine learning fundamentals and a proven ability to know when and how to apply them effectively. - Demonstrated ownership of end-to-end model productionisation, with a strong background in software engineering principles. - A bias for simplicity and a focus on achieving tangible business impact over theoretical complexity. - Exceptional programming and statistical skills, with the ability to translate ambiguous objectives into technical reality. WHY JOIN US? At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. 💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. ➡️ Want a d ... (truncated, view full listing at source)
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