Software Engineer, Machine Learning Platform - MDX
About The Position
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 You will help build high performance and flexible pipelines that can rapidly evolve to handle new technologies, techniques and modeling approaches You will work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day You will 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.
Requirements
- B.S., M.S., or PhD. in Computer Science or equivalent
- Exceptionally strong knowledge of CS fundamental concepts and OOP languages
- 2+ 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
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
Responsibilities
- 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
Benefits
- 401(k) plan with employer matching
- 16 weeks of paid parental leave
- wellness benefits
- commuter benefits match
- paid time off
- paid sick leave
- medical, dental, and vision benefits
- 11 paid holidays
- disability and basic life insurance
- family-forming assistance
- mental health program
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
