Senior Machine Learning Engineer - Recommendations
London · London, United Kingdom - Deliveroo · Full-time · Hybrid · Posted Oct 7, 2026
At a glance
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- London · London, United Kingdom - Deliveroo
About the role
- Deliveroo is looking for a Senior Machine Learning Engineer to join the London office as part of a Global DoorDash Engineering team working in a hybrid arrangement.
- This role sits in the Consumer Org, focusing on recommendation problems with direct, measurable impact on how customers discover relevant content.
- You will collaborate with experienced scientists and engineers across DoorDash, Deliveroo, and Wolt to shape the next generation of the recommendation experience.
Responsibilities
- 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.
Requirements
- 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.
- Experience with recommendation systems, ranking, retrieval, personalisation, or closely related ML problems.
- Ability to independently turn an ambiguous customer or product problem into a well-scoped ML approach, make sound trade-offs and drive it to a measurable outcome.
- Proficiency in Python and experience with modern ML frameworks and large-scale data processing.
- Understanding of how to evaluate ML systems rigorously, including offline metrics, experiment design and interpreting online results.
- Ability to communicate complex technical ideas clearly and work effectively with cross-functional partners.
Benefits
- Competitive salary
- Equity options
Workplace
- Working hybrid, 3 days in the office
Skills
- Python
- Machine Learning
- Recommendation Systems
- Ranking
- Retrieval
- Personalisation
