Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our company's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
In this role, you will help build SoCs by driving quality and reliability processes from the Integrated Circuit (IC) perspective. Working with various cross-functional teams, you will develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute test plans. Within the larger organization, you will collaborate with global hardware quality and reliability, silicon design, validation, and engineering teams. You will have an understanding of IC flows, wafer processing, testing, qualification, yield, reliability, and failure analysis.
The ML, Systems, and Cloud AI (MSCA) organization at our company designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all our company services (Search, YouTube, etc.) and our company Cloud. Our end users, Cloud customers and the billions of people who use our company services around the world.
We prioritize security, efficiency, and reliability across everything we do – from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including our company Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
Define and lead qualification hardware and test developments in front of internal teams and external vendors.
Define and execute Silicon and package qualification activities (e.g., HTOL, ELFR, ESD/LU, b/HAST, THB, etc.).
Extract, manipulate, and analyze large volumes of data from Silicon and package qualification programs (e.g., HTOL, ELFR, ESD, LU, UHAST, TCT, etc.), High Volume MFG, and field returns to identify failure mechanisms, reliability trends, and opportunities for yield, quality, and reliability improvement.
Own cross-functional investigation of IC quality and reliability issues to identify root causes and develop solutions (e.g., RMA Triage, Analytics, Failure Analysis, etc.).
Develop and implement physics-based statistical Quality and Reliability models (e.g., ELF, TDDB, NBTI, HCI, Time zero failures, etc.) to predict silicon device failure mechanisms, degradation patterns, and lifetime behaviors.
In this role, you will help build SoCs by driving quality and reliability processes from the Integrated Circuit (IC) perspective. Working with various cross-functional teams, you will develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute test plans. Within the larger organization, you will collaborate with global hardware quality and reliability, silicon design, validation, and engineering teams. You will have an understanding of IC flows, wafer processing, testing, qualification, yield, reliability, and failure analysis.
The ML, Systems, and Cloud AI (MSCA) organization at our company designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all our company services (Search, YouTube, etc.) and our company Cloud. Our end users, Cloud customers and the billions of people who use our company services around the world.
We prioritize security, efficiency, and reliability across everything we do – from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including our company Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
Define and lead qualification hardware and test developments in front of internal teams and external vendors.
Define and execute Silicon and package qualification activities (e.g., HTOL, ELFR, ESD/LU, b/HAST, THB, etc.).
Extract, manipulate, and analyze large volumes of data from Silicon and package qualification programs (e.g., HTOL, ELFR, ESD, LU, UHAST, TCT, etc.), High Volume MFG, and field returns to identify failure mechanisms, reliability trends, and opportunities for yield, quality, and reliability improvement.
Own cross-functional investigation of IC quality and reliability issues to identify root causes and develop solutions (e.g., RMA Triage, Analytics, Failure Analysis, etc.).
Develop and implement physics-based statistical Quality and Reliability models (e.g., ELF, TDDB, NBTI, HCI, Time zero failures, etc.) to predict silicon device failure mechanisms, degradation patterns, and lifetime behaviors.
Requirements:
Minimum qualifications:
Bachelor's degree in Electrical Engineering, Materials Science, a related technical field, or equivalent practical experience.
2 years of experience in IC silicon quality or reliability.
Experience in semiconductor CMOS technology, device physics, failure mechanisms, and accelerated test methodologies.
Experience in reliability modeling, data analytics, and statistics.
Preferred qualifications:
Experience in semiconductor reliability, manufacturing processes (e.g., fab, assembly, test), or IC and packaging failure mechanisms and related failure analysis.
Experience in data analytics, especially to identify commonalities and abnormalities.
Knowledge of Design-for-Reliability guidelines and implementation techniques.
Familiarity with test methods and hardware for silicon qualification (e.g., HTOL chambers, ESD, LU, etc.).
Minimum qualifications:
Bachelor's degree in Electrical Engineering, Materials Science, a related technical field, or equivalent practical experience.
2 years of experience in IC silicon quality or reliability.
Experience in semiconductor CMOS technology, device physics, failure mechanisms, and accelerated test methodologies.
Experience in reliability modeling, data analytics, and statistics.
Preferred qualifications:
Experience in semiconductor reliability, manufacturing processes (e.g., fab, assembly, test), or IC and packaging failure mechanisms and related failure analysis.
Experience in data analytics, especially to identify commonalities and abnormalities.
Knowledge of Design-for-Reliability guidelines and implementation techniques.
Familiarity with test methods and hardware for silicon qualification (e.g., HTOL chambers, ESD, LU, etc.).
This position is open to all candidates.
