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About The Team
Come help us build the world's most reliable on-demand logistics engine for delivery! We are seeking a talented Machine Learning Engineer to improve delivery service quality for DoorDash's marketplace of consumers, merchants, and dashers. DoorDash Labs is an independent team within DoorDash exploring robotics and automation to transform last-mile logistics long-term. We welcome Machine Learning Engineers, Economists, Mathematicians, Statisticians, and Senior Quantitative Researchers from all disciplines.

About The Role
As a Machine Learning Engineer, you will leverage our data and ML infrastructure to develop models impacting millions of users across our platforms. You will collaborate with engineers, analysts, and product managers to develop, iterate, and deploy models that enhance our business and customer experience.

You're Excited About This Opportunity Because You Will…

• Build production ML models to improve consumer experience by reducing errors, cancellations, and fulfillment issues.
• Manage the entire modeling lifecycle: feature creation, development, experimentation, monitoring, and maintenance.
• Explore new opportunities where delivery quality can influence demand shaping, search ranking, and customer segmentation.

We're Excited About You Because…

• You are high-energy, confident, and data-driven, with a focus on progress and growth.
• You take ownership of your work and are focused and driven.
• You are humble, receptive to feedback, and adaptable in a fast-paced environment.
• You are eager to expand your skills and carve your career in a hyper-growth setting.
• You desire to make an impact through collaboration and responsibility.

Experience
You should have:

• 3+ years of industry experience developing impactful ML models post-PhD or 5+ years post-graduate degree.
• An M.S. or PhD in Machine Learning, Statistics, Computer Science, or related fields.
• Proficiency in programming languages such as Python, SciKit-Learn, LightGBM, Spark MLlib, PyTorch, TensorFlow, etc.
• Deep understanding of complex systems like marketplaces and expertise in at least two domains among ML, causal inference, operations research, forecasting, or experimentation.
• Experience deploying production ML models and designing sophisticated experimentation techniques.
• Willingness or plans to relocate to San Francisco, CA, or Sunnyvale, CA.