Machine Learning Engineer, Computer Vision
DoorDash · San Francisco, CA | Sunnyvale, CA | Seattle, WA · 341 Executive Engineering
About this role
DoorDash is hiring a mid-level Machine Learning Engineer based in San Francisco, CA | Sunnyvale, CA | Seattle, WA. The posting calls out experience with Python, Spark, TensorFlow, 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
- San Francisco, CA | Sunnyvale, CA | Seattle, WA
- Department
- 341 Executive Engineering
More roles at DoorDash
Job description
from DoorDash careers
Come help us build the world's most reliable on-demand, logistics engine for last-mile grocery and retail delivery! We're looking for an experienced senior machine learning engineer to help us develop the cutting-edge Computer Vision models that power DoorDash's growing grocery and retail business.
About the RoleWe’re looking for a passionate Applied Machine Learning expert to join our team. As a Computer Vision expert, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the computer vision system 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 and inventory information more accurate and real time, as well as help Dasher efficiency. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multidisciplinary teams.
You’re excited about this opportunity because you will…- Develop production machine learning solutions to solve consumer vision problems such as entity recognition, entity resolution, attribute extraction, object detection, segmentation, metric learning, and category classification, image classification.
- Collaborate with cross-functional leaders across engineering, product, and business strategy to help shape a product roadmap driven by machine learning, accelerating the growth of a multi-billion-dollar retail delivery ecosystem.