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| Google USA |
About the job
As a Principal Engineer for Google Research you will be responsible for providing technical and strategy guidance to the Ecosystems Simulation team. You will collaborate with partner teams to develop simulation technology and synthetic user models to advance the practice of recommender system research and development. As simulations are promised to play an increasing role in machine learning and related fields, you will have an opportunity to build and scale the large scale simulation project and directly impact the advancement of recommender technology.Responsibilities
- Work across teams of Research Scientists, Research Engineers, and Product engineers to build up the roadmap and strategy for the Simulations project
- Identify stakeholders and onboard their existing experimental frameworks to simulations
- Design infrastructure for different simulations use cases
- Create simulated user models that mirrors aggregate distribution of behavior
- Provide leadership and guidance to ad-hoc simulation projects and move them to a unified architecture
Minimum qualifications:
- Bachelor’s degree in Computer Science, a similar technical field of study, or equivalent practical experience
- 15 years of professional experience or 13 years with an advanced degree
- Experience leading technical teams
- Experience with full stack engineering, machine learning models, and programming in one of the following: Java, C++, or Python
Preferred qualifications:
- 20 years of professional experience
- Expertise in multiple areas such as system design, machine learning, infrastructure, privacy, and product strategy
- Experience building data-driven planning platforms with multi-agent interactions
- Experience leading the development and experimentation infrastructure of a large-scale product
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Location: Mountain View, CA, USA
Company: Google
Deadline: August 14, 2021.
