The Machine Learning Engineer will join a team focused on developing and improving ETA models for DoorDash's logistics engine. This role involves leveraging robust data and machine learning infrastructure to create models that enhance the experience for consumers, merchants, and dashers. The engineer will work collaboratively with data scientists, engineers, and product managers to tackle challenging business problems. This position offers the opportunity to impact millions of users and contribute to the growth of the business.

• 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree in developing advanced machine learning models with business impact.
• Proficiency in using AI coding tools in the full software development lifecycle.
• M.S. or PhD in Computer Science, Statistics, or other related quantitative fields.
• Strong background in Deep Learning and OSS ML technologies such as Spark, PyTorch, and Airflow.
• Demonstrated expertise with programming languages such as Python and machine learning libraries.
• Deep understanding of complex systems such as Marketplaces and domain knowledge in relevant fields.
• Experience shipping production-grade ML models and designing sophisticated experimentation techniques.
• Willingness to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA.

• Build Deep Learning models for next-generation ETA that provide accurate and scalable time predictions.
• Own the modeling life cycle end-to-end, including feature creation, model development, testing, and maintenance.
• Collaborate with cross-functional teams to develop and iterate on models.
• Explore new opportunities for ETA applications in different business areas and markets.