Overview
Introduction
What is the assignment problem at DoorDash?
Overview
Introduction
What is the assignment problem at DoorDash?
Overview
Monitoring is hugely important, especially for a site like DoorDash that operates 24/7.
One of the core mottoes on the engineering team at DoorDash is:
We are only as good as our next delivery!
In May, DoorDash participated at the O’Reilly Artificial Intelligence Conference in New York where I presented on “How DoorDash leverages AI in its logistics engine.” In this post, I walk you through the core logistics problem at DoorDash and describe how we use Artificial Intelligence (AI) in our logistics engine.
Most Android apps rely on network calls to a set of backend services.
Customers come to DoorDash to discover and order from a vast selection of their favorite stores, so it is important to be able to surface what is most relevant to them.
To A/B or not to A/B, that is the question
Overview
On the Dispatch team at DoorDash, we use simulation, empirical observation, and experimentation to make progress towards our goals; however, given the systemic nature of many of our products, simple A/B tests are often ineffective due to network effects.
One of our goals at DoorDash is to surface to consumers a wide range of stores that are quickly deliverable to their given address.
At DoorDash we recently migrated the codebase of our iOS Consumer and Dasher apps to Swift 3 from Swift 2.
Customers across North America come to DoorDash to discover and order from a vast selection of their favorite stores.