Reliability Prediction Engineer
Taoyuan, Taoyuan District, Taoyuan City, Taiwan

Our computational challenges are so big, complex and unique we can't just purchase off-the-shelf hardware, we've got to make it ourselves.

Your team designs and builds the hardware, software and networking technologies that power all of Google's services. As a Hardware Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure.

You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing.

Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of Google users.

With your technical expertise, you lead projects in multiple areas of expertise (i.e., engineering domains or systems) within a data center facility, including construction and equipment installation / troubleshooting / debugging with vendors.

As a Reliability Prediction Engineer, you will develop prediction model plans, and run complex statistical methodologies in reliability.

Google's mission is to organize the world's information and make it universally accessible and useful. Only one thing consistently stands in the way between our users and the world's information hardware.

Our Consumer Hardware team researches, designs, and develops new technologies and hardware to make our user's interaction with computing faster, more powerful, and seamless.

Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, our Consumer Hardware team is making people's lives better through technology.


  • Be responsible for working with data sets and building expert prediction model that improve the performance of reliability test.
  • Work with RMA analysts to extract, transform, and analyze large data sets and work with engineers to embed models into production process.
  • Use prediction model to support the risk assessment for reliability critical issues.
  • Use prediction model to support the cost estimation by reliability test result.
  • Manage fast changing business priorities and interfacing with product managers, and engineers are required for success.
  • Minimum qualifications :

  • Master's degree in Statistics, Mathematics, Data Science, Industrial Engineering, related field, or equivalent practical experience.
  • 3 years of experience with prediction modeling, building models by reliability test.
  • 3 years of experience with data analysis and working with Weibull++ or equivalent tool.
  • 3 years of experience working with statistical analysis and tools (Python, R, SQL).
  • Preferred qualifications :

  • PhD in Statistics, Mathematics, Data Science, or Industrial Engineering.
  • 3 years of experience with prediction modeling (e.g., regression model, logistic-regression model, etc.) for RMA data and reliability data.
  • Understanding of reliability tests, including mechanical stress tests, shock / drop / vibration testing, and environmental testing.
  • Ability to support with assessments and cost estimations.
  • Excellent problem solving and communication skills.
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