Senior Machine Learning Engineer - Recommendations

About the role

Deliveroo is looking for a Senior Machine Learning Engineer to join its London office as part of a global DoorDash engineering team, working hybrid (3 days in the office). The role sits in the Consumer organisation and focuses on recommendation problems with direct, measurable impact on how customers discover restaurants, dishes, items and other content.

Key responsibilities

• Design, develop and improve recommendation, ranking and retrieval models that surface relevant restaurants, dishes, items and content.
• Own applied ML problems end to end: frame the problem, analyse 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 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 that improve recommendation quality, robustness or efficiency.
• Contribute to applied-science practice through technical reviews, knowledge sharing and thoughtful experimentation.

Required profile

• Substantial hands-on experience applying machine learning to real-world problems and a track record of moving models from development into production; a PhD with relevant applied research experience is also welcome.
• Experience with recommendation systems, ranking, retrieval, personalisation or closely related ML problems.
• Able to turn an ambiguous customer or product problem into a well-scoped ML approach, make sound trade-offs and drive it to a measurable outcome.
• Clear communication of complex technical ideas and effective collaboration with cross-functional partners.

Required skills

• Proficiency in Python and experience with modern ML frameworks and large-scale data processing.
• Rigorous evaluation of ML systems, including offline metrics, experiment design and interpretation of online results.

What we offer

• Competitive salary and equity options.
• Flexible working and a low-hierarchy, high-ownership environment.