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Machine Learning

Machine Learning

Reinforcement Learning for On-Demand Logistics

Overview Introduction What is the assignment problem at DoorDash? What is reinforcement learning? Reinforcement learned assignment Moving forward Conclusion Introduction DoorDash recently held our thirteenth hackathon. Hackathons are our opportunity to explore new technologies and moon-shot ideas; they help us stay up-to-date with the world and think 10x. At DoorDash, we’re constantly thinking of ways ...

Richard Hwang Gary Ren Yixin Tang
Machine Learning

How Artificial Intelligence Powers Logistics at DoorDash

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. LAST-MILE LOGISTICS IN A THREE-SIDED ...

Raghav Ramesh
Machine Learning

Personalized Store Feed with Vector Embeddings

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. In a previous article, Powering Search & Recommendations at DoorDash, we discussed how we built our initial personalized search and discovery experience to surface the ...

Mitchell Koch Aamir Manasawala
Machine Learning

Switchback Tests and Randomized Experimentation Under Network Effects at DoorDash

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. To be able to experiment ...

David Kastelman Raghav Ramesh
Machine Learning

Powering Search & Recommendations at DoorDash

Customers across North America come to DoorDash to discover and order from a vast selection of their favorite stores. Our mission is to surface the best stores for our consumers based on their personal preferences. However, the notion of “best stores” for a consumer varies widely based on their diet, taste, budget, and other preferences. ...

Aamir Manasawala Mitchell Koch
Machine Learning

How To Get from Salad to Sushi in 3 Moves

At DoorDash, we want to make it as easy as possible for people to discover and order from great restaurants in their neighborhoods. As part of that goal, one fascinating problem we’re tackling is how to create a personalized experience for each user on the DoorDash platform by surfacing recommendations for restaurants and other merchants ...

Mitchell Koch

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