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Hardware Reliability Engineer, Product Integrity at Google
Mountain View, United States


Job Descrption

Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Mechanical Engineering, Materials Science, or equivalent practical experience.
  • 6 years of experience in applying Design for Reliability techniques.
  • Experience with statistical analysis (e.g., Monte Carlo Analysis, DoE, SPC, Gage R&R).
  • Experience with JPM or Weibull++ for reliability modeling (e.g., lifetime distribution, degradation analysis, stress-strain analysis).

Preferred qualifications:

  • Master's degree or PhD in Hardware Engineering, Electrical Engineering, Mechanical Engineering, or Materials Science.
  • Experience with failure analysis techniques for electrical, mechanical, or optical components.
  • Experience working with overseas manufacturing partners and manufacturing processes.
  • Experience in a leadership role.
  • Ability to travel up to 20% of the time as needed.
  • Ability to summarize and communicate issues to executives.

About the job

As a Reliability Engineer, you will play a key role in creating new consumer electronic products that meet a high bar for reliability and performance. You will work closely with the product management and design engineering teams to define standards, specify tests, and then supervise test execution and failure analysis. A broad engineering background and command of statistical methods will help to inform design of new products. Your strong interpersonal and communication skills will be key to ensuring adoption of your technical recommendations.

In this role, you will develop the next-generation technologies that change how users connect, explore, and interact with information and one another. You will develop new products that are used by people. You will solve new problems as we continue to push technology forward.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

  • Develop reliability performance metrics and lead management reviews to review progress against those metrics. Lead reliability test planning, methodology, and execution for all aspects of the product.
  • Lead the failure analysis process with internal and external cross-functional teams for all failures discovered during reliability testing.
  • Work in reliability test labs and collaborate closely with Test Engineers.
  • Perform field data analysis, lead reliability testing to real world usage correlation studies, and drive the continuous improvement and refinement of reliability performance metrics.
  • Translate product management reliability goals into appropriate testable goals and perform statistical data analysis, Accelerated Life Testing (ALT) and modeling, and risk assessments.
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