Machine Learning Engineer - ETA Team
DoorDash · Sunnyvale, CA | San Francisco, CA | Seattle, WA · 341 Executive Engineering
About this role
DoorDash is hiring a mid-level Machine Learning Engineer based in Sunnyvale, CA | San Francisco, CA | Seattle, WA. The posting calls out experience with Python, Spark, Airflow, PyTorch. Compensation is listed at $137,100–$201,600 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Sunnyvale, CA | San Francisco, CA | Seattle, WA
- Department
- 341 Executive Engineering
More roles at DoorDash
Job description
from DoorDash careers
About the Team
Join us in building the world's most reliable on-demand logistics engine for delivery! We are bringing on a talented Machine Learning Engineer to help us develop and improve the ETA models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. As a fundamental area of investment for DoorDash, ETA has among the coolest problems to solve at scale and creates a major impact on the company and its businesses.
About the Role
As a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop inference and optimization ETA models that impact millions of users across our three audiences and tackle our most challenging business problems. You will work with other data scientists, engineers, and product managers to develop and iterate on models to help us grow our business and provide better service quality for our customers.
You’re excited about this opportunity because you will…
- Build Deep Learning models for next-generation ETA that provide the most accurate, scalable and robust time predictions and enhance the consumer, merchant, and dasher experience.
- Own the modeling life cycle end-to-end, including feature creation, model development and testing, experimentation, monitoring and explainability, and model maintenance.