DoorDash Engineering Blog

Learn about high impact projects that power our velocity, reliability, and innovation.

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Backend Data Machine Learning

Enabling Efficient Machine Learning Model Serving by Minimizing Network Overheads with gRPC

Learn the challenges of reducing network overheads with gRPC optimizations

Data Machine Learning

Meet Sibyl – DoorDash’s New Prediction Service – Learn about its Ideation, Implementation and Rollout

Learn how building a prediction service enables the utilization of ML models based on real-time data

Cody Zeng
Culture General

How DoorDash is Scaling its Merchant Engineering Teams to Meet New Challenges

Learn how the DoorDash merchant team has scaled up to support merchants during the Covid-19 crisis

Varsha Dudani Yvette Martinez
Machine Learning

Improving Experimental Power through Control Using Predictions as Covariate (CUPAC)

Too much varience can reducing experimental power. Learn how we solved this problem with our new CUPAC method

Jeff Li Yixin Tang Jared Bauman
Culture General

Interview with Rajat Shroff – VP of Product at DoorDash

Learn more about the product design team at DoorDash

Helena Seo
Culture General

Design Leadership Interview with Tae Kim

Learn more about what it means to be a product designer at DoorDash

Will DiMondi
Machine Learning

DoorDash’s ML Platform – The Beginning

Learn how we increased the scalability and productivity of the data science team by building a machine learning platform

Param Reddy
Culture General

Product Leadership Interview with Kevin Fu

Learn about the DoorDash product organization: their mission goals and culture

Taleen Shekerijan
Culture General

Design Leadership Interview with Radhika Bhalla

Learn what its like to be a UX researcher at DoorDash from our head of UX, Radhika Bhalla

Helena Seo
Culture General

Design Leadership Interview with Will DiMondi

Learn more about the design team at DoorDash

Helena Seo
Machine Learning

Supercharging DoorDash’s Marketplace Decision-Making with Real-Time Knowledge

DoorDash is a dynamic logistics marketplace that serves three groups of customers: Merchant partners who prepare food or other deliverables, Dashers who carry the deliverables to their destinations,  Consumers who savor a freshly prepared meal from a local restaurant or a bag of groceries from their local grocery store.  For such a real-time platform as ...

Animesh Kumar Dawn Lu Sri Santhosh Hari
Backend Machine Learning

Next-Generation Optimization for Dasher Dispatch at DoorDash

Learn how we optimized dasher selection using data science

Holly Jin Josh Wien Sifeng Lin

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