Description
Join Deliveroo's London office as a Senior Machine Learning Engineer in the Global DoorDash Engineering team, working hybrid. You'll focus on recommendation problems with direct impact on customer content discovery, collaborating with teams across DoorDash, Deliveroo, and Wolt.
Responsibilities
- Design, develop, and improve recommendation, ranking, and retrieval models for surfacing relevant content to customers.
- Own applied ML problems end-to-end: framing problems, analyzing data, developing models, defining offline evaluation, running experiments, and monitoring production performance.
- Develop methods balancing relevance with product and customer needs, such as diversity, availability, and business constraints.
- Collaborate with Software Engineers, ML Engineers, Product Managers, and Analysts to turn scientific insights into reliable products.
- Evaluate and apply state-of-the-art ML methods to improve recommendation quality, robustness, or efficiency.
- Contribute to high standards of applied-science practice through technical reviews, knowledge sharing, and experimentation.
Requirements
- Substantial hands-on experience applying machine learning to real-world problems and a track record of bringing models into production.
- Experience with recommendation systems, ranking, retrieval, personalization, or related ML problems.
- Ability to independently turn ambiguous problems into scoped ML approaches and drive them to measurable outcomes.
- 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 and experiment design.
- Clear communication of complex technical ideas and effective work with cross-functional partners.
Benefits
- Competitive salary and equity options
- Opportunity to solve meaningful problems at scale
- Fast impact and shipping of ideas in a low-hierarchy environment
- Growth through challenge and ownership
- Culture built for builders with high standards, collaboration, flexible working, and continuous learning