Senior Machine Learning Engineer - Recommendations

About this role

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do.

Our Global 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. We're looking for a Senior Machine Learning Engineer to join our London office as part of a Global DoorDash Engineering team (working hybrid, 3 days in the office). This role sits in our Consumer Org, where you'll work on recommendation problems with direct, measurable impact on how customers discover relevant content.

You’ll collaborate with experienced scientists and engineers across DoorDash, Deliveroo and Wolt, learning from multiple recommendation systems while helping shape the next generation of the experience. What You'll Be Doing Design, develop and improve recommendation, ranking and retrieval models that surface relevant restaurants, dishes, items and content to customers. Own applied ML problems end to end: frame the problem, analyze data, develop models, define offline evaluation, run experiments and monitor production performance.

Develop methods that balance relevance with product and customer needs, such as diversity, availability, business constraints and changing user intent. Collaborate closely with Software Engineers, ML Engineers, Product Managers and Analysts to turn scientific insights into reliable customer-facing products. Evaluate and apply state-of-the-art ML methods where they meaningfully improve recommendation quality, robustness or efficiency.

Contribute to a high bar for applied-science practice through technical reviews, knowledge sharing and thoughtful experimentation. What You'll Need to Thrive You have substantial hands-on experience applying machine learning to real-world problems and a track record of bringing models from development into production; a PhD with relevant applied research experience is equally welcome. You have experience with recommendation systems, ranking, retrieval, personalisation, or closely related ML problems.