Staff Software Engineer, Machine Learning

About the Team

DoorDash is building the world's most reliable on-demand, logistics engine for delivery. We are continuing to grow rapidly and expanding our Engineering offices globally!

About the Role

As a Software Engineer, Machine Learning, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph at the heart of our fast-growing grocery and retail delivery business. You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product knowledge graph accurate, standardized, semantically rich, easily discoverable, and extensible. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multi-disciplinary teams. This role is hybrid with some in-office time expected and will report to an Engineering Manager.

Responsibilities

• 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 (e.g., 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.

Qualifications

• M.S., or PhD. in a technical field such as computer science, mathematics, statistics, physics or equivalent.
• 8+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software.
• 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.

Benefits

• 401(k) plan with employer matching
• 16 weeks of paid parental leave
• Wellness benefits
• Commuter benefits match
• Paid time off and paid sick leave in compliance with applicable laws (e.g., Colorado Healthy Families and Workplaces Act)
• Medical, dental, and vision benefits
• 11 paid holidays
• Disability and basic life insurance
• Family-forming assistance
• Mental health program
• Flexible paid time off/vacation, plus 80 hours of paid sick time per year for salaried roles
• For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g., about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g., about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week)

Pay

The national base pay range for this position within the United States, including Illinois and Colorado, is $203,500—$299,300 USD. In addition to base salary, the compensation includes opportunities for equity grants.