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DoorDash is seeking a Machine Learning Engineer for the Drive team to own ML systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration.
You will build next-generation ML models for delivery ETA, pickup ETA, and merchant prep-time estimation, and apply reinforcement learning to improve logistics decisions and marketplace efficiency. We also explore AI-native experiences using LLMs and vision-language models.
DoorDash Drive powers deliveries placed through merchants' own channels—including their websites, mobile apps, and phone orders—using DoorDash's logistics network. The Drive Machine Learning team builds the prediction and intelligence systems that power this business, including delivery and pickup time estimation, merchant prep-time prediction, order release optimization, logistics decision‑making, and AI‑powered delivery quality signals.
Drive presents a unique machine learning challenge. Every merchant has different operational workflows, preparation patterns, and customer expectations, requiring models that generalize across millions of deliveries while adapting to highly diverse merchant behavior. Our team has significant opportunities to improve prediction accuracy, optimize logistics decisions, and build AI‑native experiences that directly improve merchant, consumer, and dasher outcomes.
As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration.
Your work will span several high-impact problem areas: