machine learning engineer for recommendations

Deliveroo; Greater London; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Equity options

Flexible working

Job summary

Deliveroo — глобальная инженерная команда, создающая и масштабирующая системы для миллионов пользователей, рестораны и курьеры участвуют в трёхсторонней экосистеме.

Задачи охватывают разработку и улучшение моделей рекомендаций, ранжирования и поиска контента, внедрение моделей в продакшн и мониторинг. Соискатель будет работать с инженерами, PM и аналитиками, чтобы превращать научные идеи в надёжные продукты для клиентов.

Qualifications

• Hands-on ML in production
• Experience with recommender systems or related ML problems
• Proficiency in Python and ML frameworks
• Strong evaluation of ML models including offline metrics
• Ability to translate ambiguous problems into scoped ML approaches

Responsibilities

• Design, develop, and improve recommendation, ranking, and retrieval models
• Own applied ML problems end to end from framing to production monitoring
• Develop methods balancing relevance with product needs and business constraints
• Collaborate with Software Engineers, ML Engineers, PMs, and Analysts
• Evaluate state-of-the-art ML methods to improve quality and efficiency
• Contribute to applied-science practices through reviews and knowledge sharing

Skills

Hands-on ML in production

Python

Cross-functional communication

Recommendation systems

Large-scale data processing

Education

PhD (optional)

Tools

ML frameworks

Job description

Описание

Deliveroo is part of DoorDash and operates a global, three-sided marketplace serving customers, riders, and partners. Its Global Engineering teams build and scale systems for millions of people, while its Consumer organization helps customers discover relevant content.

Задачи

• Design, develop, and improve recommendation, ranking, and retrieval models that surface relevant restaurants, dishes, items, and content to customers
• Own applied machine learning problems end to end, from problem framing and data analysis to model development, offline evaluation, experimentation, and production monitoring
• Develop methods that balance relevance with product and customer needs, including 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 machine learning methods when they meaningfully improve recommendation quality, robustness, or efficiency
• Contribute to applied‑science practices through technical reviews, knowledge sharing, and thoughtful experimentation

Требования

• Substantial hands‑on experience applying machine learning to real‑world problems and bringing models from development into production; relevant applied research experience with a PhD is also welcome
• Experience with recommendation systems, ranking, retrieval, personalisation, or closely related machine learning problems
• Ability to independently turn an ambiguous customer or product problem into a well‑scoped machine learning approach, make sound trade‑offs, and drive it to a measurable outcome
• Proficiency in Python and experience with modern machine learning frameworks and large‑scale data processing
• Understanding of rigorous machine learning evaluation, including offline metrics, experiment design, and interpreting online results
• Ability to communicate complex technical ideas clearly and work effectively with cross‑functional partners

Условия

• Competitive salary and equity options
• Flexible working