National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning Engineer - Operational Research (London)

Deliveroo
London
2 days ago
Create job alert

Social network you want to login/join with:

Machine Learning Engineer - Operational Research, London

col-narrow-left

Client:

Deliveroo

Location:

London, United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

col-narrow-right

Job Reference:

7b74143f5c92

Job Views:

5

Posted:

22.06.2025

Expiry Date:

06.08.2025

col-wide

Job Description:

The Data & Science Org

At Deliveroo, we have a world-class data and science organisation with a mission to enable the highest quality human and machine decision-making.

We work throughout the company - in product, business and platform teams to answer some of the most interesting questions out there. For example, how can we connect restaurants, riders and customers most efficiently in order to deliver food as quickly as possible? How do data and technology help restaurants to grow as consumer habits change? How can we predict what someone wants to order for dinner long before the idea has even crossed their mind?

These are just some of the tough problems we are solving at Deliveroo. There is no challenge that cannot be yours; the scope for growth and personal impact is enormous. Data Scientists and Machine Learning Engineers at Deliveroo belong to an expert, thoughtful, and active community with guest lecturers, a robust technical review process, a career progression framework, and plenty of opportunities to learn new things.

The Role

As a Machine Learning Engineer, you will play a crucial role in the development, implementation and maintenance of cutting-edge machine learning products. Your responsibilities will involve engineering sophisticated machine learning models, as well as refining and updating existing systems.

In this team, you will develop the algorithmic and machine-learning systems that power Deliveroo’s delivery network. You will work in a cross-functional team alongside engineers, data scientists and product managers to develop systems that make automated decisions at massive scale. The team has independence and works on some of the most interesting problems at the intersection of riders, consumers, and restaurants. We evaluate the performance of all our decision-making machines through our world-class experimentation platform.

You will:

  • Optimise our delivery network by making rider assignment decisions; predicting how long a leg of the delivery journey will take; or mitigating real-time delays.
  • Enhance our simulation capabilities to more accurately predict the effects of algorithmic changes on our delivery network.
  • Optimise consumer and rider fees.

Also, you will work alongside people who work on:

  • The consumer experience by showing the most relevant restaurants and dishes.
  • Detecting fraud and abuse from consumers, riders, and restaurants.
  • Assisting restaurants in optimising their presence on Deliveroo, for example by recommending that they improve their menus or photography, or add a popular dish.
  • Creating an ML platform to improve our ML and optimisation capabilities.

You will report into a ML/OR Manager. This is a hybrid role that will be based inLondon.

Requirements:

  • You are someone who knows the fundamentals of machine learning and operational research and when they should be applied through a relevant PhD or work experience.
  • You can translate fuzzy logistics and delivery problems or objectives into a well-thought-out algorithmic solution. You get satisfaction from seeing your algorithms shipped and driving measurable impact to the business.
  • Experience in programming, where the work involves programming with Python, Rust and Go.
  • Experience in discrete event simulations and/or combinatorial optimisation problems.
  • Understand end-to-end model productionisation.
  • A bias to simplicity, where you care most about achieving impact.

Nice to haves:

  • Experience in solving Vehicle Routing Problems (VRP) and/or building large scale delivery network simulations
  • Experience in any of the following areas: algorithms and data structures, parallel and distributed computing, high-performance computing

Why Deliveroo

Our mission is to transform the way you shop and eat, bringing the neighbourhood to your door by connecting consumers, restaurants, shops and riders. We are transforming the way the world eats and shops by making access to food and products more convenient and enjoyable. We give people the opportunity to buy what they want, as they want it, when and where they want it.

We are a technology-driven company at the forefront of the most rapidly expanding industry in the world. We are still a small team, making a very large impact, looking to answer some of the most interesting questions out there. We move fast, value autonomy and ownership, and we are always looking for new ideas.

At Deliveroo we know that people are the heart of the business and we prioritise their welfare. Benefits differ by country, but we offer many benefits in areas including healthcare, well-being, parental leave, pensions, and generous annual leave allowances, including time off to support a charitable cause of your choice. Benefits are country-specific, please ask your recruiter for more information.

Diversity

At Deliveroo, we believe a great workplace is one that represents the world we live in and how beautifully diverse it can be. That means we have no judgement when it comes to any one of the things that make you who you are - your gender, race, sexuality, religion or a secret aversion to coriander. All you need is a passion for (most) food and a desire to be part of one of the fastest-growing businesses in a rapidly growing industry.

We are committed to diversity, equity and inclusion in all aspects of our hiring process. We recognise that some candidates may require adjustments to apply for a position or fairly participate in the interview process. If you require any adjustments, please don't hesitate to let us know. We will make every effort to provide the necessary adjustments to ensure you have an equitable opportunity to succeed.

Please click to view our candidate privacy policy.


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer - Bioimage Data & Agentic Systems

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.