Software Engineer - Machine Learning Infrastructure - USDS
Seattle, Washington, United States
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About the team
The mission of our AML team is to push the next-generation AI infrastructure and recommendation platform for the ads ranking, search ranking, live & ecom ranking in our company. We also drive substantial impact on core businesses of the company. Currently, we are looking for Machine Learning Engineer - Machine Learning Infrastructure to join our team to support and advance that mission.
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
Responsibilities:
- Responsible for the design and implementation of a global-scale machine learning system for feeds, ads and search ranking models.
- Responsible for improving use-ability and flexibility of the machine learning infrastructure.
- Responsible for improving the workflow of model training and serving, data pipelines, storage system and resource management for multi-tenancy machine learning systems.
- Responsible for designing and developing key components of ML infrastructure and mentoring interns.
The mission of our AML team is to push the next-generation AI infrastructure and recommendation platform for the ads ranking, search ranking, live & ecom ranking in our company. We also drive substantial impact on core businesses of the company. Currently, we are looking for Machine Learning Engineer - Machine Learning Infrastructure to join our team to support and advance that mission.
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
Responsibilities:
- Responsible for the design and implementation of a global-scale machine learning system for feeds, ads and search ranking models.
- Responsible for improving use-ability and flexibility of the machine learning infrastructure.
- Responsible for improving the workflow of model training and serving, data pipelines, storage system and resource management for multi-tenancy machine learning systems.
- Responsible for designing and developing key components of ML infrastructure and mentoring interns.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
Engineering Jobs
Machine Learning Jobs
Tags: Data pipelines Machine Learning ML infrastructure Model training Pipelines
Region:
North America
Country:
United States
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