Product Quality Engineer, Global Hardware Quality and Reliability

In this role, you'll ensure the flawless operation of hardware systems like AI computers, networking gear, and data storage from the initial concept through end-of-life.

You'll collaborate with internal teams and manufacturing partners to build quality into every stage of product development, establish robust processes, and track and resolve field issues. This position requires a deep understanding of modern data center hardware, including design, manufacturing, and testing.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Minimum qualifications:

• Bachelor's degree in Mechanical Engineering, Industrial Engineering, Materials Engineering, a related engineering discipline, or equivalent practical experience.
• 5 years of experience in Quality/Reliability/Production operation, with direct experience in New Product development and qualification.

Preferred qualifications:

• Master's degree or PhD in Electrical, Mechanical, Industrial, Materials, or other relevant engineering fields.
• Experience with Contract Manufacturing (CM) quality management.
• Experience with advanced analytics tools like JMP/Minitab or equivalent and experience using programming languages like SQL/Python or equivalent to identify and root cause issues.
• Experience in leading successful cross-functional teams for continuous quality issue investigation and quality improvement using practical approaches (e.g. Six Sigma, Lean Sigma, Quality Metrics, DOE, SPC) and with a proven track record of strong technical leadership, and executive communication.
• Knowledge of manufacturing processes and test/debug methods.