Role Description & Responsibilities
Machine Learning
About Deliveroo
Deliveroo is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Machine Learning role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Global Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day.
We're looking for a Machine Learning Engineer to join our London office as part of a Global DoorDash Engineering team (working hybrid, 3 days in the office).
Key Responsibilities & Day-to-Day Scope
- ✓ Build and improve ranking models for vertical landing pages (grocery, retail), deciding what a user sees first when they land on a store page
- ✓ Design models that blend new-vertical content into a homepage built around restaurant ordering, without disrupting the core experience
- ✓ Build personalisation models that translate a user's existing 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
Official Qualifications & Technical Requirements
- • Minimum 3+ years of experience as an ML Engineer or Data Scientist, with a proven ability to write high-quality production code in Python
- • 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; exposure to causal inference or uplift modelling is a genuine plus but not expected
Preferred Skills & Technology Stack
- + Familiarity with MLOps pipelines (Docker, Kubernetes, Kubeflow, Triton Inference Server).
- + Knowledge of distributed training techniques and GPU acceleration (CUDA).
- + Relevant coursework, research publication, or open-source contribution in ML/DL.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Deliveroo
Verified EmployerDeliveroo champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.