ML Engineer Intern – Build Production-Ready Models

ML Engineer Intern – Build Production-Ready Models

Full-Time 20000 - 30000 £ / year (est.) No working from home possible
Deliveroo

At a Glance

  • Tasks: Build and deploy machine learning models that impact millions of users.
  • Company: Join Deliveroo, a leading tech company in the food delivery industry.
  • Benefits: Gain hands-on experience, mentorship, and potential full-time offers after the internship.
  • Other info: In-person internship at Deliveroo's London HQ for 12-24 weeks.
  • Why this job: Work on real-world ML problems with a supportive community of experts.
  • Qualifications: Pursuing a degree in Computer Science or related fields; Python and ML framework skills required.

The predicted salary is between 20000 - 30000 £ per year.

Deliveroo is a great place to start your career as a Machine Learning Engineer because you’ll work on real problems, at real scale, alongside some of the brightest technical minds working in applied machine learning today. We have a brilliant ML community with 50 MLEs based in London alongside a further 200 Data Scientists, Data Analysts and Analytics Engineers. Here, you’ll be embedded in a product team, paired with experienced engineers, supported by a strong ML community, and responsible for owning and launching machine learning models in production.

To do this, you’ll have the support of peers, mentors, and a manager who shares best practices, reviews work, and actively mentors early‑career talent. The problems we work on are genuinely complex. We operate a three‑sided marketplace, handle large volumes of real‑time data, and deploy machine learning models that directly affect how millions of people discover food, place orders, get deliveries, and receive support. Your work will be grounded in real‑world constraints and trade‑offs, not toy datasets or academic exercises.

If you’re interested in applied machine learning that ships to production, has measurable impact, and is built collaboratively rather than in isolation, this is a strong place to learn fast.

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. Applicants must be authorised to work in the U.K. to be considered for this position. The 2026 internship programme will be hosted in person at Deliveroo’s London headquarters at Cannon Bridge House, with requirements to be in office 5 days a week. This opportunity will be a 12‑24 week summer placement.

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.

We Expect That You…

  • Are working towards a BSc/MSc/PhD in Computer Science, AI, ML, NLP, Statistics or a related field
  • Have a mastery of Python and one ML framework (Tensorflow, Pytorch, MLFlow)
  • Have experience in research and in solving analytical problems
  • Are a strong communicator and team player
  • Have a passion for applied ML
  • Must be comfortable regularly exercising discretion and independent judgment in performing job duties, including evaluating options, making informed decisions, and determining appropriate courses of action within the scope of assigned responsibilities.

At Deliveroo, people are at the heart of what we do. We offer a wide range of benefits across health, wellbeing, learning and development, and financial support. 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 judgment 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.

ML Engineer Intern – Build Production-Ready Models employer: Deliveroo

Deliveroo is an exceptional employer for aspiring Machine Learning Engineers, offering a vibrant work culture where innovation thrives. Interns will gain hands-on experience in a dynamic environment, supported by a strong community of over 200 data professionals, and have the opportunity to work on impactful projects that shape the future of food delivery. With a commitment to diversity and employee growth, Deliveroo provides a unique platform for learning and collaboration, making it an ideal place to kickstart your career.

Deliveroo

Contact Details:

Deliveroo Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land ML Engineer Intern – Build Production-Ready Models

Tip Number 1

Network like a pro! Reach out to current or former Deliveroo employees on LinkedIn. Ask them about their experiences and any tips they might have for landing the internship. A personal connection can make all the difference!

Tip Number 2

Prepare for technical interviews by brushing up on your Python skills and ML frameworks like TensorFlow or PyTorch. Practice coding challenges and be ready to discuss your past projects. We want to see your passion for applied machine learning!

Tip Number 3

Showcase your projects! If you've worked on any relevant machine learning projects, make sure to highlight them in your conversations. Discuss the impact of your work and how it relates to real-world problems, just like those at Deliveroo.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team and eager to contribute to the exciting work happening at Deliveroo.

We think you need these skills to ace ML Engineer Intern – Build Production-Ready Models

Data Analysis
Machine Learning
Python
Research
Statistics
Pytorch
Tensorflow

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the ML Engineer Intern role. Highlight relevant projects, skills, and experiences that align with the job description. We want to see how your background fits into our world of applied machine learning!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to express your passion for machine learning and why you’re excited about working at Deliveroo. Let us know how you can contribute to our team and what you hope to learn during your internship.

Showcase Your Projects:If you've worked on any machine learning projects, make sure to showcase them in your application. Whether it's a personal project or something from your studies, we love seeing practical applications of your skills. It gives us a glimpse into your problem-solving abilities!

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets to the right people. Plus, it shows us you’re serious about joining our team at Deliveroo. We can’t wait to see what you bring to the table!

How to prepare for a job interview at Deliveroo

Know Your ML Frameworks

Make sure you brush up on your knowledge of Python and the ML frameworks mentioned in the job description, like TensorFlow or PyTorch. Be ready to discuss your experience with these tools and how you've used them in past projects.

Understand the Business Impact

Deliveroo is all about real-world applications of machine learning. Familiarise yourself with how ML can optimise delivery logistics or enhance customer experiences. Think of examples where ML has made a tangible difference in similar industries.

Prepare for Technical Questions

Expect to face technical questions that assess your problem-solving skills and understanding of machine learning concepts. Practice explaining your thought process clearly and concisely, as communication is key in a team environment.

Show Your Passion for Collaboration

Since you'll be working closely with experienced engineers and product teams, highlight your teamwork skills. Share examples of how you've collaborated on projects and how you value feedback and mentorship in your learning journey.