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How DoorDash Fosters Meaningful Engineering Career Development

How DoorDash fosters meaningful engineering career development

Machine Learning

How DoorDash Improves Holiday Predictions via Cascade ML Approach

Learn how DoorDash optimizes supply and demand forecasts using a cascade machine learning approach for enhanced accuracy during holidays. Discover how this innovative technique, combining Gradient Boosting and linear models, ensures operational efficiency, top-notch customer experiences, and seamless Dasher interactions.

Chad Akkoyun Zainab Danish

BPFAgent: eBPF for Monitoring at DoorDash

Learn how DoorDash uses eBPF to monitor vital networking traffic in its Kubernetes clusters.


How DoorDash Migrated from StatsD to Prometheus

Learn how DoorDash migrated to Prometheus

Machine Learning

How DoorDash Built an Ensemble Learning Model for Time Series Forecasting

In real-world forecasting applications, it is a challenge to balance accuracy and speed. We can achieve high accuracy by running numerous models and configuration combinations and we gain speed through running fast, computationally inexpensive models. We explore a number of models and configuration combinations at DoorDash to forecast demand on our platform. However, the challenge ...

Qiyun Pan Hanyu Yang

How DoorDash uses XcodeGen to eliminate project merge conflicts

At DoorDash, we work to implement efficient processes that can mitigate common conflicts within a large iOS development team. Part of those efforts involve using XcodeGen, a command line interface (CLI), to reduce merging conflicts within our various iOS teams. Here we will discuss its implementation to manage the intricate business scenarios and demanding requirements ...

Md Al Mamun Michael Thole

Unleashing Your Potential: 5 Strategies to Identify Breakout Leadership Opportunities in Tech

Contrary to popular belief that the key to an exceptional career is the accumulation of skills and experience over time, I believe that taking advantage of breakout opportunities is a game-changer in your career. Characterized by their high-visibility or high-impact nature, these breakout opportunities can propel your career to new heights as you meet their ...

Gayatri Iyengar
AI & ML Machine Learning

DoorDash identifies Five big areas for using Generative AI

In the wake of ChatGPT and Generative AI DoorDash is identifying ways this new technology can enhance the customer’s ordering experience on the platform. The company is exploring the use of Generative AI, a subset of Artificial Intelligence that generates novel content based on existing data, and how it can be implemented effectively with consideration ...

Alok Gupta

Using Metrics Layer to Standardize and Scale Experimentation at DoorDash

Learn how DoorDash build a metrics layer to enable consistent metrics and democratized decision making for experimentation

Arun Balasubramani

2022 Summer Intern Projects Article #3

Learn about more of our 2022 summer intern projects in this third article of our series.

Rini Vasan Peyton Chen William Louis Amrita Rajan

Using CockroachDB to Reduce Feature Store Costs by 75%

While building our ML feature store we learned that a mix of databases yields significant gains in efficiency and operational simplicity.

Brian Seo Kunal Shah

Failure Mitigation for Microservices: An Intro to Aperture

Learn how centralizing service monitoring and controlling into a single system improves upon individual service level mitigation efforts

Cong Ma Matt Ranney

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