Software Engineer, Machine Learning Infrastructure

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented engineers to help us create and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash's three-sided marketplace of consumers, merchants, and dashers.

At DoorDash, our Data Scientists and ML Engineers have the opportunity to dive into a wealth of delivery data to improve company-wide ML workflows such as Search & Recommendations, Dasher Assignment, ETA Prediction, and Dasher Capacity Planning. You will join a small team to build systems that empower efficient machine learning at scale. This is a hybrid opportunity in San Francisco, Sunnyvale or Seattle.

You're excited about this opportunity because you will: • Build a world-class ML platform where models are developed, trained, and deployed seamlessly • Work closely with Data Scientists and Product Engineers to evolve the ML platform as per their use cases • Help build high performance and flexible pipelines that can rapidly evolve to handle new technologies, techniques and modeling approaches • Work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day • Help design and drive directions for the centralized machine learning platform that powers all of DoorDash's business • Improve the reliability, scalability, and observability of our training and inference infrastructure

We're excited about you because: • B.S., M.S., or PhD. in Computer Science or equivalent • Exceptionally strong knowledge of CS fundamental concepts and OOP languages • 4+ years of industry experience in software engineering • Prior experience building machine learning systems in production such as enabling data analytics at scale • Prior experience in machine learning - you've developed and deployed your own models - even if these are simple proof of concepts • Systems Engineering - you've built meaningful pieces of infrastructure in a cloud computing environment. Bonus if those were data processing systems or distributed systems

Nice To Haves: • Experience with challenges in real-time computing • Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure • Familiar with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow • Familiar with Spark, MLLib, Databricks, MLFlow, Apache Airflow, Dagster and similar related technologies • Familiar with large language models like GPT, LLAMA, BERT, or Transformer-based architectures • Familiar with a cloud based environment such as AWS

DoorDash cares about you and your overall well-being. That's why we offer a comprehensive benefits package for all regular employees that includes a 401(k) plan with an employer match, paid time off, paid parental leave, wellness benefits, and several paid holidays.

Additionally, for full-time employees, DoorDash offers medical, dental, and vision benefits, disability and basic life insurance, family-forming assistance, a commuter benefit match, and a mental health program, among others.