Staff Machine Learning Engineer

Responsibilities

• Lead the design, development, and deployment of large-scale production ML systems for real-time decisioning
• Own ML systems for assignment and fulfillment estimation
• Define architectures and set modeling and deployment standards
• Lead 0→1 ML initiatives and influence technical direction across multiple teams
• Establish best practices for model development, deployment, monitoring, and governance
• Mentor other engineers and raise the technical bar for logistics ML
• Define DoorDash’s AI vision for logistics, including LLM-inspired foundation models

Requirements

• 8+ years of industry experience building and deploying production-scale machine learning systems
• Strong machine learning fundamentals applied to large-scale production systems
• Proficiency in Python
• Hands-on experience with modern ML and deep learning frameworks
• Experience designing, launching, and operating mission-critical ML models in production
• Proven ability to lead complex technical projects end to end
• Experience with knowledge distillation from large teacher models into efficient production models
• Experience with large-scale ML models in domains like recommendation, ads, marketplace, or logistics

About the Company

DoorDash is a technology and logistics company on a mission to empower local economies. We optimize how deliveries are planned and executed across the full delivery lifecycle to improve customer experience, merchant outcomes, and Dasher efficiency.