Machine Learning - DoorDash Engineering Blog

Newest Article

Machine Learning Lifecycle of a Successful ML Product: Reducing Dasher Wait Times

Read how DoorDash's product development life cycle works in this new ML blog post about how we optimized when orders are sent to merchants

Rita Golovonevsky

Ram Tripathi

13 Minute Read

Machine Learning

Solving for Unobserved Data in a Regression Model Using a Simple Data Adjustment

Learn how our team optimized prep time estimates while overcoming censored data

Sri Santhosh Hari 9 Minute Read

Data Machine Learning

Improving Online Experiment Capacity by 4X with Parallelization and Increased Sensitivity

To speed up the development of new features we needed a way to increase our experiment capacity. Learn how we improved it by 4X

Jessica Zhang

Yixin Tang 13 Minute Read

Data Machine Learning

How DoorDash is Scaling its Data Platform to Delight Customers and Meet our Growing Demand

Learn the challenges and best practices to successfully growing a data platform organization

Sudhir Tonse 26 Minute Read

Machine Learning

Leveraging Causal Modeling to Get More Value from Flat Experiment Results

Using Heterogeneous Treatment Effects to improve personalization

Mitchell Koch

Jared Bauman 15 Minute Read

Machine Learning

Retraining Machine Learning Models in the Wake of COVID-19

When the COVID-19 pandemic significantly changed how people took their meal, DoorDash had to retrain demand prediction machine learning models.

Austin Cai 12 Minute Read

Data Machine Learning

Supporting Rapid Product Iteration with an Experimentation Analysis Platform

DoorDash engineers built Curie, a new experimentation analysis platform, to better gauge the success of product experiments.

Arun Balasubramani 10 Minute Read

Machine Learning

Using a Human-in-the-Loop to Overcome the Cold Start Problem in Menu Item Tagging

Learn how we built a classification model quickly, cheaply, and at scale

Abhi Ramachandran 19 Minute Read

Machine Learning

Optimizing DoorDash’s Marketing Spend with Machine Learning

Learn how we utilized cost curves to automate our marketing campaigns at scale

Aman Dhesi 12 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