When it comes to reducing variance in experiments, the spotlight often falls on sophisticated methods like CUPED (Controlled Experiments Using Pre-Experiment Data).
Category Archives: engineering
Building DoorDash’s product knowledge graph with large language models
DoorDash’s retail catalog is a centralized dataset of essential product information for all products sold by new verticals merchants – merchants operating a business other than a restaurant, such as a grocery, a convenience store, or a liquor store.
Setting up Kafka multi-tenancy
Real-time event processing is a critical component of a distributed system’s scalability.
Improving ETAs with multi-task models, deep learning, and probabilistic forecasts
The DoorDash ETA team is committed to providing an accurate and reliable estimated time of arrival (ETA) as a cornerstone DoorDash consumer experience.
Introducing DoorDash’s in-house search engine
We reviewed the architecture of our global search at DoorDash in early 2022 and concluded that our rapid growth meant within three years we wouldn’t be able to scale the system efficiently, particularly as global search shifted from store-only to a hybrid item-and-store search experience.
Experiment Faster and with Less Effort
Business Policy Experiments Using Fractional Factorial Designs
At DoorDash, we constantly strive to improve our experimentation processes by addressing four key dimensions, including velocity to increase how many experiments we can conduct, toil to minimize our launch and analysis efforts, rigor to ensure a sound experimental design and robustly efficient analyses, and efficiency to reduce costs associated with our experimentation efforts.
Cassandra Unleashed: How We Enhanced Cassandra Fleet’s Efficiency and Performance
In the realm of distributed databases, Apache Cassandra stands out as a significant player.
Meeting DoorDash Growth with a Self-Service Logistics Configuration Platform 
DoorDash has grown from executing simple restaurant deliveries to working with a wide variety of businesses, ranging from grocery, retail and pet supplies.
Staying in the Zone: How DoorDash used a service mesh to manage data transfer, reducing hops and cloud spend
There have been many benefits gained through DoorDash’s evolution from a monolithic application architecture to one that is based on cells and microservices.
Personalizing the DoorDash Retail Store Page Experience
The DoorDash retail shopping experience mission seeks to combine the best parts of in-person shopping with the power of personalization.