Senior Software Engineer, Machine Learning

Found in: Talent US C2 - 2 weeks ago

San Francisco, United States DoorDash Full time

About the Role

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.

As a Senior 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. 

You're excited about this opportunity because you will...

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.

We're excited about you because you have...

5+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative fieldsExperience 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.Experiences in any of the following areas are preferred but not required: Online advertisingSearch relevance & rankingRecommendation system

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