Machine Learning Intern

Job Description

The Role

As a Machine Learning Engineer intern at Deliveroo, you’ll work on a well-scoped machine learning project within a product or platform team. The goal of the internship is not independent research. It is to help you learn how machine learning systems are designed, built, evaluated, and deployed in a real production environment.

The Team

Depending on the team you join, you might work on:

• Consumer & Marketplace – Ranking, search, and recommendation systems that decide which restaurants, dishes, grocery and retail items to show; personalisation and pricing models that optimise fees, promotions, and loyalty while balancing growth and profitability.
• Delivery & Logistics – Real‑time decision systems that assign riders to orders, route and schedule deliveries, and predict travel and prep times; forecasting and simulation models that plan demand, rider supply, staffing, and financial performance.
• Restaurants, Grocery & Retail (New Verticals) – Models that grow and optimise our merchant ecosystem, from catalogue and inventory quality to upsell and cross‑sell, helping partners improve menus, pricing, photography, and overall presence on Deliveroo.
• Advertising & Monetisation – Ad ranking, relevance, bidding, and budget‑optimisation models that maximise advertiser performance and marketplace revenue while preserving a great customer experience.
• Customer Care, Trust & Safety – LLM‑ and ML‑powered systems for customer support automation, sentiment and intent understanding, fair compensation and refund decisions, and fraud and abuse detection.
• ML & Agentic AI Platforms – Core ML and Agentic AI infrastructure: training, deployment, evaluation, experimentation, and safety tooling used by product teams across Deliveroo to build, monitor, and improve production ML and GenAI systems.
  

What You’ll Get Out Of This Internship

• Hands-on experience working on production ML systems
• Close mentorship from experienced Machine Learning Engineers
• Exposure to how ML is applied at scale in a fast-moving product environment
• The chance to:
• own a piece of a defined project and present your work to the team
• contribute and execute on research ideas that can be applied and used to improve product experiences
• collect, analyse, and synthesise findings from data and use these insights to build relevant ML models
• write clean, efficient, and sustainable code

If the internship goes well, there is the potential for a full-time offer at the conclusion of it.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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