# How Deliveroo Built Its Machine Learning Platform

DevFeed: [How Deliveroo Built Its Machine Learning Platform](<https://devfeed.tech/articles/deliveroo-s-machine-learning-platform-powering-the-future-of-ml-19716.md>)

Original publisher: [Read original article](<https://deliveroo.engineering/2025/07/02/deliveroo-ml-platform.html>)

Author: Saikrishna Desaraju

Published: 2025-07-02T00:00:00Z

Content type: article

Language: en

Sources: [Deliveroo](<https://devfeed.tech/sources/deliveroo.md>)

Topics: [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [distributed-training](<https://devfeed.tech/topics/distributed-training.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Python](<https://devfeed.tech/topics/python.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>), [Tensorflow](<https://devfeed.tech/topics/tensorflow.md>)

Tags: [aws](<https://devfeed.tech/tags/aws.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [distributed-training](<https://devfeed.tech/tags/distributed-training.md>), [inference](<https://devfeed.tech/tags/inference.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [machine-learning-platform](<https://devfeed.tech/tags/machine-learning-platform.md>), [python](<https://devfeed.tech/tags/python.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [rest](<https://devfeed.tech/tags/rest.md>), [tensorflow](<https://devfeed.tech/tags/tensorflow.md>)

## AI overview

Deliveroo describes its machine learning platform for standardizing model-building and deployment workflows. The platform combines open-source tools, in-house components, Kubernetes on AWS EKS, TensorFlow, PyTorch, Metaflow, and Argo; it also supports GPU and distributed training and includes Inferoo for real-time model predictions.

## Source excerpt

Enter Deliveroo's ML Platform For the past three years, we have been building Deliveroo's Machine Learning Platform, or the ML Platform as we like to call it. The ML Platform boosts our model-building and deployment capabilities by standardising ML workflows, streamlining the end-to-end development process and simplifying model deployment. Besides saving software engineering effort through centralising tooling, the ML Platform also reduces the time that our ML engineers spend on infrastructure tasks. As a result, our ML engineers can now iterate their ML models 2-3x faster than before. What makes our ML Platform tick? At the core of our ML Platform lies a carefully curated tech stack - an integrated suite of infrastructure tools, services, and libraries. It blends robust open source technologies with purpose-built, in-house components. Key open source tools include Kubernetes, Argo, and Metaflow, all seamlessly connected with leading ML frameworks like TensorFlow and PyTorch. We choose mature, community-driven solutions and actively contribute back where we can. This entire ecosystem is powered by AWS, running on EKS, and anchored by our data warehouse. In the sections that follow, we'll take a closer look at the key components that drive our ML Platform. Metaflow To give ML engineers seamless access to scalable compute on Kubernetes, we use Metaflow, a powerful Python library that helps break down complex model-building workflows into smaller, manageable jobs. These jobs are orchestrated by Argo, one of the backbone tools in our infrastructure. One of Metaflow's biggest strengths is its flexibility. It allows engineers to move effortlessly between local development, staging on Kubernetes, and production deployment--helping teams iterate quickly as they experiment and scale. Recently, we added support for GPUs and distributed training, enabling faster training times and the ability to work with much larger datasets. Inferoo For models that require real-time predictio