Staff Software Engineer, Machine Learning

DoorDash, Inc.; San Francisco, Sunnyvale, New York, Seattle (CA, CA, NY, WA); Hybrid; USD 204,000 - 299,000; Full time

Benefits offered by this job

401(k) plan with employer matching

16 weeks of paid parental leave

wellness benefits

commuter benefits match

paid time off and paid sick leave

Job summary

DoorDash, Inc. is seeking a Software Engineer, Machine Learning to design, implement, and validate algorithmic improvements to our catalog system and product knowledge graph. You will leverage production ML pipelines to make our ads and product knowledge more accurate, standardized, and easily discoverable.

Hybrid role with in-office time, reporting to an Engineering Manager. The role requires strong ML expertise, production experience, and collaboration with multidisciplinary teams to deliver

Qualifications

• 8+ years ML industry experience with strong fundamentals.
• Experience with production ML lifecycle and tools.
• Experience building scalable data/feature pipelines with PySpark and Snowflake SQL.
• Experience with ML frameworks such as PyTorch, Keras, LightGBM, scikit-learn, Spark ML.

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 bid density and market competitiveness impact on value and revenue.
• Develop new data solutions (embeddings and consumer profiles) to target the relevant audience.
• Be responsible for the end-to-end ML lifecycle, including ideation, offline training, online deployment, experimentation, and monitoring.
• Build and extend data/ML infrastructure to empower Ads data applications (data analysis, ML modeling, experimentation).
• Scale systems and services to fuel business growth.

Skills

ML algorithms

Production ML lifecycle

Data pipelines

End-user problem solving

Education

MS/PhD in CS/Math/Statistics/Physics

Tools

Pyspark

Snowflake SQL

PyTorch

Keras

LightGBM

scikit-learn

Spark ML

Job description

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! We are looking for Software Engineers, Machine Learning to build and maintain a large scale 24x7 global infrastructure system that powers DoorDash's 3-sided marketplace of Consumers, Merchants and Dashers.

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 (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.

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.

Compensation

The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants.

The national base pay range for this position within the United States, including Illinois and Colorado. $203,500 - $299,300 USD

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

See below for paid time off details: For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. 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).

Diversity & Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

Statement of Non-Discrimination

In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ance