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Machine Learning

Improving ETAs with Multi-Task Models, Deep Learning, and Probabilistic Forecasts

DoorDash improves ETA accuracy by developing a NextGen ML System

Chi Zhang Lewis Warne Ziqi Jiang Qingyang Xu Hubert Jenq Jianzhe Luo Backend

Introducing DoorDash’s In-House Search Engine

Empowering Seamless Searches: DoorDash develops an in-house search engine using Lucene for enhanced search capabilities

Konstantin Shulgin Satish Saley Anish Walawalkar Machine Learning

Experiment Faster and with Less Effort

DoorDash Unveils Innovative Framework: Fractional Factorial Design Accelerating Business Policy Experiments.

Yicong ("Nicole") Lin Yixin Tang Backend

Cassandra Unleashed: How We Enhanced Cassandra Fleet’s Efficiency and Performance

Optimizing Cassandra performance for cost savings and increased efficiency.

Seed Zeng Backend

Meeting DoorDash Growth with a Self-Service Logistics Configuration Platform 

DoorDash evolves from restaurant deliveries to a diverse business portfolio by using a robust logistics platform.

Saurabh Gupta Reid Arwood Backend

Staying in the Zone: How DoorDash used a service mesh to manage  data transfer, reducing hops and cloud spend

DoorDash’s engineering teams use a service mesh to realize data transfer cost savings without sacrificing service quality.

Hochuen Wong Levon Stepanian Machine Learning

Personalizing the DoorDash Retail Store Page Experience

Discover how DoorDash's recommendation systems deftly navigate the vast retail product space to delight consumers with a personalized shopping journey.

Luming Chen Yuan Meng Anthony Zhou General

Atlantis Hardening and Review Fatigue

Explore the nuances of using infrastructure-as-code (IaC) with PR automation when making infrastructure changes.

Dmitriy Dunin Ron Waisberg Data

API-First Approach to Kafka Topic Creation

DoorDash revamps Kafka Topic creation which reduces real-time pipeline onboarding time and saves countless developer hours.

Varun Chakravarthy Basar Onat Seed Zeng Luke Christopherson Mobile

How DoorDash Manages Mobile Releases

DoorDash’s consumer iOS team manages the complexities of release management at scale.

Manolo Sañudo 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 Backend

Privacy Engineering at DoorDash Drive

DoorDash Drive explors geomasking user addresses to protect privacy while maintaining local analytic capabilities.

Alex Dougherty

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