Senior Product Quality Engineer, GHQR

Minimum qualifications:

• Bachelor's degree in Mechanical Engineering, Industrial Design, or Manufacturing, a related field, or equivalent practical experience.
• 8 years of experience in quality, manufacturing or product engineering of cloud hardware technology or electronic hardware systems.
• 5 years of experience working on PCB assembly, design validation, component qualification, data analysis, and scripting.
• 5 years of experience interacting with and manipulating data using SQL.

Preferred qualifications:

• Master's degree or PhD in Electrical, Mechanical, Industrial, Materials, or a related engineering field.
  
• Experience setting up manufacturing assembly processes, driving product launches and assembly process optimization within manufacturing operations.
  
• Experience in technical leadership, project management, and executive communication.
  
• Experience in managing an engineering or operation team.
• Experience working with contract manufacturing partners.
• Ability to conduct failure analysis on complex multi-physics issues with cross-functional teams, and work with engineering analysis software (e.g., MATLAB, JMP, and Python).

About the job

Google's custom-designed machines make up one of the largest and most powerful computing infrastructures in the world. The Hardware Testing Engineering team ensures that this cutting-edge equipment is reliable. In the R&D lab, you design test equipment for prototypes of our machinery and develop the protocols used to scale these tests for the entire global team. Working closely with design engineers, you give input on designs to improve our hardware until you're sure it meets Google's standards of quality and reliability.

Google's Cloud infrastructure is one of the world's most advanced compute, network, and AI platforms, providing customers with speed, efficiency, intelligence, and high reliability. The Cloud Supply Chain and Operations team ensures this technical infrastructure is delivered with speed, reliability, and efficiency.

Quality and reliability are core values, crucial to deliver our customers with exceptional products and services. The Global Hardware Quality and Reliability (GHQR) team is responsible for accelerating end-to-end product introduction and delivering predictable product quality and reliability, directly contributing to Google's competitive advantage.

In this role, you will lead quality initiatives for our AI infrastructure. You will ensure the flawless operation of hardware systems like AI computers, networking gear, and data storage from initial concept through end-of-life.

You will collaborate with internal teams and manufacturing partners to build quality into every stage of product development, establish processes, and track and resolve field issues.

Role may require travel within US and internationally up to 25% of time.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

The US base salary range for this full-time position is $144,000-$209,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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.

Responsibilities

• Own the overall product quality process, spanning internal and external development through successful deployment and production at scale, ensuring consistent quality across all stages.
  
• Develop predictive failure models using advanced statistical methods. Track key quality metrics and extract actionable insights using advanced analytics and statistical methods.
  
• Lead the resolution of product issues during manufacturing and field operations using structured problem solving techniques such as eight discipli