Machine Learning Engineer Lead - Merchant

Doordash San Francisco , CA 94118

Posted 5 days ago

About the Team

Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop the AI/ML to power DoorDash growing Merchants.

About the Role

You will be leading a team of world-class engineers in Machine Learning science, redefining Merchant experience through cutting edge approaches, and providing a consistent, personalized experience to our merchants, no matter where they sit on their journey with us.

In this role, you will utilize our robust data and machine learning infrastructure to develop inference and optimization for Merchant experience and build new merchant's products, such as deep learning based logistic service for restaurants and non-restaurants, AI solutions to make our catering product successful, menu item tax categorization, expanding our merchant selection on DoorDash. You will partner cross functionally to set the strategies that help us grow our business and lead efforts to execute those strategies.

You're excited about this opportunity because you will…

  • Lead the effort for Merchant machine learning: Applying supervised, semi-supervised, LLM, Deep Learning, Multi-modality AI to improve or Merchant experience and build new merchant's products

  • Lead the team to build AI powered products for restaurants onboarding, build logistic ETA that provides the most accurate and robust time prediction for non-restaurants DoorDash logistics service, improve tax categorization prediction.

  • Lead with engineering and product leaders to shape the product roadmap leveraging AI/ML.

  • Lead a team to implement end to end ML products, and ship both real time and batch production models via experimentation.

  • Find and propose new ways to drive business impact and solve complex problems through state of the art ML and GenAI

  • Hire, grow and mentor a talented team of Machine Learning Scientists

You can find out more on our ML blog


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