Staff Machine Learning Engineer, Fulfillment Planning

The role

You will lead the design, development, and deployment of large-scale production machine learning systems for the fulfillment ecosystem. You will own ML systems for assignment and fulfillment estimation to improve delivery quality, cost, and efficiency.

What you will do

• Own and build foundational ML systems for delivery quality and logistics efficiency
• Work on real-time assignment, routing, and fulfillment estimation
• Lead 0 to 1 ML initiatives
• Influence architecture and strategy for Tier-0 logistics services
• Collaborate with Product, Data Science, and Platform Engineering
• Establish best practices for model development, deployment, monitoring, retraining, and governance
• Define and lead an LLM-inspired foundation model for logistics
• Mentor other engineers

Required qualifications

• 8+ years of industry experience building and deploying production-scale machine learning systems
• Strong machine learning fundamentals
• Fluent in Python
• Hands-on experience with modern ML frameworks, especially deep learning frameworks
• Experience designing, launching, and operating mission-critical ML models or systems in production
• Ability to lead complex technical projects end to end
• Ability to communicate clearly with technical and non-technical audiences
• Comfortable operating in ambiguous problem spaces

Nice to have

• Experience building or shipping large-scale ML models for recommendation, ads, marketplace, or logistics

Benefits

• 401(k) plan with employer matching
• 16 weeks of paid parental leave
• Wellness benefits
• Commuter benefits match
• Paid time off
• Paid sick leave
• Medical, dental, and vision benefits
• 11 paid holidays
• Disability and basic life insurance
• Family-forming assistance
• Mental health program

About the company

DoorDash is a technology and logistics company that aims to empower local economies. The company is growing rapidly and works to expand from food delivery to delivering any and all goods.