Machine Learning - DoorDash Engineering Blog

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AI & ML Data Machine Learning Transforming MLOps at DoorDash with Machine Learning Workbench

DoorDash builds an internal ML Workbench by taking a user-centered approach to solve for productivity and velocity of our Data, ML, AI teams.

Archit Jha

Nachiket Paranjape

10 Minute Read

Backend Data Machine Learning

Enabling Efficient Machine Learning Model Serving by Minimizing Network Overheads with gRPC

Learn the challenges of reducing network overheads with gRPC optimizations

ArbazKhan 17 Minute Read

Data Machine Learning

Meet Sibyl – DoorDash’s New Prediction Service – Learn about its Ideation, Implementation and Rollout

Learn how building a prediction service enables the utilization of ML models based on real-time data

Cody Zeng 11 Minute Read

Machine Learning

Improving Experimental Power through Control Using Predictions as Covariate (CUPAC)

Too much varience can reducing experimental power. Learn how we solved this problem with our new CUPAC method

Jeff Li

Yixin Tang

Jared Bauman 9 Minute Read

Machine Learning

DoorDash’s ML Platform – The Beginning

Learn how we increased the scalability and productivity of the data science team by building a machine learning platform

Param Reddy 8 Minute Read

Machine Learning

Supercharging DoorDash’s Marketplace Decision-Making with Real-Time Knowledge

DoorDash is a dynamic logistics marketplace that serves three groups of customers: Merchant partners who prepare food or other deliverables, Dashers who carry the deliverables to their destinations, Consumers who savor a freshly prepared meal from a local restaurant or a bag of groceries from their local grocery store. For such a real-time platform as ...

Animesh Kumar

Dawn Lu

Sri Santhosh Hari 8 Minute Read

Backend Machine Learning

Next-Generation Optimization for Dasher Dispatch at DoorDash

Learn how we optimized dasher selection using data science

Holly Jin

Josh Wien

Sifeng Lin 8 Minute Read

Machine Learning

Organizing Machine Learning: Every Flavor Welcome!

Learn how we organized our ML team including its vision, values and organizational structure

Alok Gupta 7 Minute Read

Machine Learning

Personalized Cuisine Filter

The consumer shopping experience is a key focus area at DoorDash. We want to provide consumers an enjoyable shopping experience by providing the right recommendation to the right consumer at the right time for the right location. On our app, there are cuisine filters on the top of the explore page. We have built a ...

Max Li

Xiaochang Miao 7 Minute Read

Machine Learning

Analyzing Switchback Experiments by Cluster Robust Standard Error to Prevent False Positive Results

Within the dispatch team of DoorDash, we are making decisions and iterations every day ranging from business strategies, products, machine learning algorithms, to optimizations. Since all these decisions are made based on experiment results, it is critical for us to have an experiment framework with rigor and velocity. Over the last few years, we have ...

Yixin Tang

Caixia Huang 10 Minute Read

Machine Learning

Experiment Rigor for Switchback Experiment Analysis

At DoorDash, we believe in learning from our marketplace of Consumers, Dashers, and Merchants and thus rely heavily on experimentation to make the data-driven product and business decisions. Although the majority of the experiments conducted at DoorDash are A/B tests or difference-in-difference analyses, DoorDash occasionally relies on a type of experimentation internally referred to as ...

Carla Sneider

Yixin Tang 14 Minute Read

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 11 Minute Read

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 2 Minute Read