When DoorDash added a pickup option for customers, complementing our existing delivery service, we needed to build a map to ensure a smooth user experience.
Category Archives: engineering
Supporting Rapid Product Iteration with an Experimentation Analysis Platform
DoorDash’s new experimentation platform, built on a combination of SQL, Kubernetes, and Python, allows for quick iteration of data-driven feature improvements.
Eliminating Task Processing Outages by Replacing RabbitMQ with Apache Kafka Without Downtime
Scaling backend infrastructure to handle hyper-growth is one of the many exciting challenges of working at DoorDash.
Using a Human-in-the-Loop to Overcome the Cold Start Problem in Menu Item Tagging
Companies with large digital catalogs often have lots of free text data about their items, but very few actual labels, making it difficult to analyze the data and develop new features.
Building a system that can support machine learning (ML)-powered search and discovery features while simultaneously being interpretable enough for business users to develop curated experiences is difficult.
Four Challenges When Launching a Product Partnership
DoorDash discusses four best practices when launching a product partnership.
A Framework For Speedy and Scalable Development Of Android UI Tests
Learn how a Fluent Design pattern can improve your automated UI testing development.
Building Reliable Workflows: Cadence as a Fallback for Event-Driven Processing
Amid the hypergrowth of DoorDash’s business, we found the need to reengineer our platform, extracting business lines from a Python-based monolith to a microservices-based architecture in order to meet our scalability and reliability needs.
Scaling DoorDash’s Geospatial Innovation with a Location-Based Delivery Simulator
DoorDash’s Geo team built a delivery simulator to automate a formerly manual process of testing new location-based logic on our platform.
Avoiding Conditional Navigation Pitfalls When Implementing the Android Navigation Library
Navigation between mobile application screens is a core part of the user experience.
Optimizing DoorDash’s Marketing Spend with Machine Learning
Over a hundred years ago, John Wanamaker famously said “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half”.