Staff Machine Learning Engineer, Fulfillment Planning
Core
Building large-scale production ML systems for real-time decisioning in DoorDash's fulfillment ecosystem, optimizing assignment, routing, batching, and cost.
Role type
Staff Machine Learning Engineer (Logistics)
Builds
Core assignment engine, real-time ETA/estimation systems, and optimization algorithms for grocery, retail, parcel, and catering.
Domain
Food delivery logistics and supply chain optimization
Deliverable
production ML models
Required skills
Python, deep learning frameworks, production ML system design, model monitoring/retraining/governance, knowledge distillation, end-to-end project leadership, cross-functional stakeholder influence, 0→1 system building
Preferred skills
Experience with recommendation/marketplace/logistics domains, LLM-inspired foundation models for logistics
Technologies
Python, deep learning frameworks
Responsibilities
Design and deploy large-scale production ML systems for assignment and fulfillment estimation; define technical direction and best practices for logistics ML; mentor engineers; lead 0→1 ML initiatives; influence architecture for Tier-0 services.
Seniority
Staff, hands-on IC with strategic influence
