DoorDash is seeking a Software Engineer specializing in Machine Learning to enhance its global logistics engine. The role involves developing and maintaining a large-scale infrastructure that supports DoorDash's marketplace. The engineer will focus on improving the product knowledge graph and implementing machine learning solutions to optimize advertising efficiency. This hybrid position requires collaboration with multi-disciplinary teams and a strong command of production-level machine learning.

• M.S. or PhD in a technical field such as computer science, mathematics, statistics, or physics.
• 3+ years of machine learning industry experience with a solid understanding of algorithms.
• Experience building data and feature engineering pipelines at scale using Pyspark and Snowflake SQL.
• Experience with building machine learning systems in production using frameworks such as PyTorch, Keras, or scikit-learn.

• Develop advanced machine learning models to improve ads efficiency and quality.
• Design and build optimization algorithms for budget pacing and automated bidding.
• Establish a data-driven framework to understand bid density and market competitiveness.
• Develop new data solutions to target relevant audiences.
• Manage the end-to-end machine learning lifecycle including ideation and deployment.
• Build and extend the current data and machine learning infrastructure.