About The Position

Core Compute Analytics is a team of data scientists and software engineers with the mission of improving the efficiency and performance of the ecosystem and of Google Cloud Platform. In this role, you will build data pipelines to deliver production hints that improve efficiency and allow Google to achieve fleet-wide optimization goals and develop statistical modeling frameworks that allow Google to effectively manage its infrastructure spending. You will define compute telemetry needs and munge the data to strategically decide which projects infrastructure teams should pursue as they strive to enable new capabilities for Google. The current issues include increasing heterogeneity in the fleet arising from the end of Moore's law and the introduction of Machine Learning (ML) accelerators as well as the divergence between the efficiency goals of internal Google workloads and Google Cloud Platform.

Requirements

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field or equivalent practical experience.
  • 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.

Nice To Haves

  • 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.

Responsibilities

  • Formulate and solve the statistical problems that arise from the large scale deployment of novel compute technologies.
  • Present your results and recommendations to Engineering Leadership, helping them to understand the opportunity space and trade-offs.
  • Have high visibility within the technology organization by partnering with teams throughout Technical Infrastructure, Google Cloud Platform, and Core Systems.
  • Develop technical metrics, statistical models, simulation frameworks, data pipelines, and experiments.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service