DoorDash

Technology

StaffMachineLearningEngineer,FulfillmentPlanning

$137–299k San Francisco, California, United States
The Brief

“Staff Machine Learning Engineer, Fulfillment Planning at DoorDash. Skills: Machine Learning, Production Systems, Logistics Optimization, Architecture. Lead design, development, deployment of ML systems. Own ML systems for assignment, fulfillment estimation”

What You'll Achieve.

Improve customer experience; Improve merchant outcomes; Improve Dasher efficiency; Improve DoorDash profitability; Improve fulfillment quality; Reduce fulfillment cost; Improve delivery quality; Improve delivery cost; Improve logistics efficiency

Industry & Context.

Technology
Problems you'll solve

Operating in ambiguous problem spaces; Turning 0→1 ideas into production systems

What They're Looking For.

Must Have

8+ years of industry experience building and deploying production-scale machine learning systems, Machine learning fundamentals, Fluent in Python, Hands-on experience with modern ML frameworks, Designed, launched, and operated mission-critical ML models or systems in production, Lead complex technical projects end to end, Communicate clearly with both technical and non-technical audiences, Comfortable operating in ambiguous problem spaces, Built or shipped large-scale ML models for recommendation, ads, marketplace, logistics, or other domains, Experience with knowledge distillation from large teacher models into efficient production models

Nice to Have

Deep learning frameworks

What You'll Do.

deployment of ML systems

Own ML systems for assignment

fulfillment estimation

Improve delivery quality

Contribute to batching

fulfillment execution

Set modeling standards

Set deployment standards

Mentor other engineers

Shape ML application in logistics

Define AI vision for logistics

Build foundational ML systems

How You'll Work.

Team & Collaboration

Partnering closely with Product, Data Science, Engineering, Platform teams; Collaborate closely with Product, Data Science, Platform Engineering; Highly cross-functional environment

Communication Scope

Communicate clearly with both technical and non-technical audiences

Process & Methodology

Lead complex technical projects end to end

Free ATS check

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