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

Desirable

• Machine learning engineers on the Ads team have the opportunity to dive into a wealth of consumer and merchant data, and leverage advanced machine learning techniques to maximize the value for our consumers, advertisers, and Doordash
• Develop advanced machine learning models to improve ads efficiency and quality
• Design and build optimization algorithms for budget pacing and automated bidding to achieve various advertising goals
• Establish a data-driven framework to understand how the bid density and market competitiveness would affect advertising value and platform revenue
• Develop new data solutions (eg. embeddings and consumer profiles) to target the relevant audience
• Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement
• Build and extend the current data/ML infrastructure to empower Ads data applications including data analysis, ML modeling, and experimentation
• Scale our systems and services to fuel the growth of our business