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Software Engineer - Model Serving Infrastructure - USDS
Team Intro
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 - Model Serving 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 distributed inference infrastructure for feeds, ads and search ranking models.
- Responsible for building monitoring/managing tools to oversee the reliability and scalability of online inference servers
- Responsible for triaging system inefficiency and bottlenecks and improving system performance
- Responsible for building tools to analyze bottlenecks and sources of instability and then design and implement solutions
- Responsible for collaboration with product teams and providing general solutions to meet their requirements
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 - Model Serving 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 distributed inference infrastructure for feeds, ads and search ranking models.
- Responsible for building monitoring/managing tools to oversee the reliability and scalability of online inference servers
- Responsible for triaging system inefficiency and bottlenecks and improving system performance
- Responsible for building tools to analyze bottlenecks and sources of instability and then design and implement solutions
- Responsible for collaboration with product teams and providing general solutions to meet their requirements