Recommendation systems provide highly personalized results, but building hyperpersonalized experiences remains challenging because of the bottlenecks created by content generation and presentation.
Category Archives: Optimization
Supercharging DoorDash logistics through causal ML and joint optimization
DoorDash’s delivery drivers — called Dashers — may be offered incentives such as peak pay (extra money) to improve supply during particularly busy times, in specific areas.
Using LLMs to build content embeddings for search and recommendations
Header Image Description: Example of semantic meaning beyond engagements
A persistent bottleneck has constrained search and recommendation functions at DoorDash for years — the caliber of content embedding depends on data quality, while personalization depends on embedding quality.
Smarter promotions with causal machine learning
In August 2025 at the KDD AI Conference in Toronto, Canada, we presented our published research, “Causal Machine Learning for Promotions: Industry Evidence and Applications.” In this paper, we describe a two-stage framework for improving promotion efficiency through causal machine learning – first by estimating each customer’s true response to different offers, and then by optimizing which promotions to deliver under practical business constraints.
Using LLMs to infer grocery preferences from DoorDash restaurant orders
Consumers enjoy DoorDash deliveries from a variety of merchants, ranging from restaurants to pet stores.
Building an anomaly detection platform at DoorDash to catch fraud trends early
Fraud doesn’t always kick the door down.
A scalable LLM approach to enhancing chatbot knowledge with user-generated content
DoorDash’s support chatbot handles a huge volume of questions from Dashers and customers every day.
Advancing Menu Content with AI: How DoorDash uses AI to generate menu descriptions
Our mission at DoorDash is to empower local businesses of all sizes to thrive and grow in the digital age.
How DoorDash leverages LLMs to evaluate search result pages
At DoorDash, delivering relevant and high-quality search results is essential to ensure that customers find what they’re looking for quickly and effortlessly.
Augmenting Fuzzy Matching with Human Review to Maximize Precision and Recall
Even state-of-the-art classifiers cannot achieve 100% precision.