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Causal Machine Learning Engineer at DoorDash - ApplyBlast

Causal Machine Learning Engineer

DoorDash

2 months ago

San Francisco, California, United States

Onsite

Full Time

Senior

0 applicants

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About this role

DoorDash is seeking a Causal Machine Learning Engineer to develop and productionize causal ML systems that drive decisions across its New Verticals marketplace. The role involves building uplift and heterogeneous treatment effect models, creating counterfactual evaluation frameworks, and integrating experimentation data with ML decisioning to improve promotions, ranking, and consumer growth.

Responsibilities

Design and productionize causal ML systems for marketplace decisions
Develop counterfactual evaluation frameworks for ranking and promotions
Partner with econometrics and analytics leaders to select appropriate causal methods

Skills

About DoorDash

doordash.com

Headquarters

San Francisco, California, United States

Company Size

10001+ employees

Founded

2013

View Profile

DoorDash is a last‑mile logistics and on‑demand delivery platform that connects consumers with local restaurants, grocers, convenience stores, and other merchants through its marketplace and mobile apps. It operates consumer services (ordering and DashMart), a merchant toolkit for order management and analytics, a subscription service (DashPass), and DoorDash Drive for white‑label or large‑scale delivery. Deliveries are fulfilled by a network of independent drivers (“Dashers”) and optimized with routing and logistics technology across the U.S. and select international markets. The company positions itself as a technology partner for local commerce, helping merchants reach customers via flexible fulfillment and data-driven tools.