21 hours ago
Base Salary
$168k - $247k/yr
Responsibilities
- Develop advanced machine learning models to improve core team capabilities.
- Own the end-to-end ML lifecycle, including ideation, offline training, online shadowing and deployment, experimentation, and post-launch monitoring and measurement.
- Create novel ML and AI solutions for the catalog system and product knowledge graph.
- Build and scale data, feature engineering, ML systems, and services supporting the business.
- Own projects end-to-end, collaborate with multidisciplinary teams, and mentor junior and mid-level engineers.
Requirements
- Master’s or PhD in a technical field such as computer science, mathematics, statistics, or physics, or equivalent.
- 5+ years of machine learning industry experience with strong knowledge of ML algorithms and fundamentals.
- Proficiency using AI coding tools such as Claude Code, Codex, or Cursor throughout the software development lifecycle.
- Experience building data and feature engineering pipelines at scale using PySpark and Snowflake SQL.
- Experience building production machine learning systems using frameworks such as PyTorch, Keras, LightGBM, scikit-learn, or Spark ML.
Benefits
- Hybrid work arrangement with some in-office time expected.
- Base salary range of $167,800–$246,800 USD, plus opportunities for equity grants.
- 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off, and paid sick leave.
- Medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program.
- Flexible paid time off and 80 hours of paid sick time per year for salaried roles.
Tech Stack
Categories
About DoorDash
DoorDash builds a marketplace and logistics platform that connects consumers with local restaurants and retailers for on-demand delivery and pickup, powered by a network of independent Dashers. It earns through delivery fees, merchant commissions, advertising, DashPass subscriptions, and white-label fulfillment via DoorDash Drive. Founded in 2013 and headquartered in San Francisco, the public company operates across the U.S. and selected international markets, and also researches automation through DoorDash Labs.