ML Engineer - Personalisation & Ranking (Hybrid, London)

Deliveroo PLC

Greater London

Hybrid

GBP 90,000 - 130,000

Full time

3 days ago
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Job summary

Deliveroo PLC in London is seeking a Machine Learning Engineer to join our Global DoorDash Engineering team. This role is hybrid, with 3 days in the office, and focuses on building ranking and personalisation models across verticals for our marketplace used by millions of customers, riders and partners.

You will design and productionise end-to-end models, focusing on impact and simplicity, with opportunities to influence recommendations and content blending across the home and store experiences.

Qualifications

  • 3+ years of experience as ML Engineer or Data Scientist.
  • Experience with end-to-end model productionisation.
  • A bias to simplicity, where you care most about achieving impact.
  • Background in personalisation, ranking, or recommender systems.

Responsibilities

  • Build and improve ranking models for vertical landing pages (grocery, retail) to decide what a user sees first when landing on a store page.
  • Design models that blend new-vertical content into a homepage built around restaurant ordering without disrupting core experience.
  • Build personalisation models that translate user behaviour into relevant recommendations for verticals they haven't tried yet.
  • Contribute to notification targeting — who gets notified, with what message, and when, to drive adoption of new verticals.

Skills

Python
Model productionisation
Personalisation
Ranking/recommender

Job description

Deliveroo PLC in London is seeking a Machine Learning Engineer to join our Global DoorDash Engineering team. This role is hybrid, with 3 days in the office, and focuses on building ranking and personalisation models across verticals for our marketplace used by millions of customers, riders and partners.

You will design and productionise end-to-end models, focusing on impact and simplicity, with opportunities to influence recommendations and content blending across the home and store experiences.

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