Staff Software Engineer, Machine Learning

<div class="content-intro"><p><img style="display: none; max-width: 100%;" src="https://click.appcast.io/greenhouse-te8/a31.png?ent=34&amp;e=22630&amp;t=1701374353806" width="1px"> <img style="display: none; max-width: 100%;" src="https://track.jobadx.com/v1/i.gif?utm_pixel=224e990b-8ff4-4287-8d5d-2ff09647f181&amp;utm_ptz=EST&amp;utm_rqt=track" alt="" width="1"></p></div><h2><strong>About the Team</strong></h2> <p>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.</p> <h2><strong>About the Role</strong></h2> <p>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.&nbsp; 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.</p> <p>This role is hybrid with some in-office time expected and will report to an Engineering Manager.&nbsp;</p> <h2><strong>You're excited about this opportunity because you will...</strong></h2> <ul> <li>Develop advanced machine learning models to improve ads efficiency and quality.</li> <li>Design and build optimization algorithms for budget pacing and automated bidding to achieve various advertising goals.&nbsp;</li> <li>Establish a data-driven framework to understand how the bid density and market competitiveness would affect advertising value and platform revenue.&nbsp;</li> <li>Develop new data solutions (eg. embeddings and consumer profiles) to target the relevant audience.</li> <li>Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement.</li> <li>Build and extend the current data/ML infrastructure to empower Ads data applications including data analysis, ML modeling, and experimentation.</li> <li>Scale our systems and services to fuel the growth of our business.</li> </ul> <h2><strong>We're excited about you because you have...</strong></h2> <ul> <li>M.S., or PhD. in a technical field such as computer science, mathematics, statistics, physics or equivalent.</li> <li>8+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.</li> <li>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</li> <li>Experience building data/feature engineering pipelines at scale using Pyspark and Snowflake SQL.</li> <li>Experience with building machine learning systems in production by using frameworks such as PyTorch, Keras, LightGBM, scikit-learn, Spark ML, or related.</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p><span style="font-size: 32px;"><strong>Compensation</strong></span></p> <p>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.</p> <p>In addition to base salary, the compensation for this r