• Perform custom silicon package-level yield analysis, correlation data analysis, and yield improvement, leveraging AI applications to automate insights.

• Drive cross-functional readiness for New Product Introduction (NPI), resolve technical bottlenecks in materials, processes, and equipment to ensure seamless scaling to mass production.

• Oversee early production site qualifications and lead continuous improvement programs (CIP) to optimize SLT yield and process stability.

• Lead root cause analysis for technical gaps and excursions, partner with suppliers to establish statistical process capabilities that guarantee high-quality delivery.

• Work with cross-functional teams on failure analysis and debug of field issues and deliver engineering data and reports supporting return material authorization (RMA) process.

In this role, you will join the team responsible for high volume custom silicon manufacturing from NPI through product ramp, sustaining, and end-of-life (EOL) System Level Test (SLT) yield analysis and process improvement and scrap optimization, manufacturing performance, quality and excursion management and prevention, value engineering, change control management, new production site qualifications for alternate sourcing and business continuity. HVM capacity readiness, cycle time optimization and more.

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.

• Bachelor’s degree or equivalent practical experience.

• 5 years of experience in program management.

• Experience as a semiconductor process and system level test (SLT) product test engineer within a semiconductor industry.

• Experience in data analysis using semiconductor production data, and in developing AI based applications and Application Programming Interface (API) development using Python.