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Required Senior SoC Hardware Quality and Reliability Engineer
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
We're the driving force behind our 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 Cloud, Global Networking, Data Center operations, systems research, and much more.
Responsibilities
Own technical specifications, architectural definitions, and physical power-on of custom qualification vehicles (HTOL load boards, ESD fixtures, latch-up rigs). Drive external layout vendors to achieve seamless electrical correlation with ATE environments.
Govern execution quality of applied stresses, define electrical, thermal, and telemetry parameters on test vehicles to ensure uniform, valid stress profiles without unintended overstress or setup artifacts.
Lead the end-to-end engineering delivery lifecycle for qualification hardware, map and drive critical cross-functional dependencies across internal validation and product engineering teams to ensure on-time readiness.
Serve as the primary technical interface for external PCB layout houses, fabrication shops, and component suppliers; manage design reviews, track lead times, and enforce delivery schedules.
Lead laboratory troubleshooting for qualification hardware anomalies; isolate setup/socket faults from true silicon failures and drive supplier corrective actions (CAPA) when board excursions occur.

Required SoC Quality and Reliability Engineer, Cloud
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
Our data centers are the most advanced in the world. In this role, you will help build the state-of-the art SoCs that power these data centers by driving quality and reliability processes from the Integrated Circuit perspective. This is an opportunity to create silicon and follow it into the field (and back!) to drive improvements for the next-generations of chips.
In this role, you will understand Integrated circuit (IC) flows, wafer processing, testing, qualification, yield, reliability, and failure analysis. You will work with various cross-functional teams to develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute and test plans. Within the larger organization you will collaborate with global hardware quality and reliability teams, silicon design, validation and engineering teams.The AI and Infrastructure team is redefining whats possible. We empower customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity.
Responsibilities
Drive the strategic definition and development of Design-for-Reliability (DfR) guidelines, collaborating with cross-functional subject matter experts to integrate reliability into early design stages.
Define and lead the development of qualification hardware and test methodologies, managing internal teams and external vendors to ensure robust silicon and package verification.
Execute comprehensive silicon and package qualification programs (including HTOL, ELFR, ESD/LU, b/HAST, etc.) and conduct in-depth failure analysis to resolve quality issues.
Extract and analyze large-scale data from qualification programs, high-volume manufacturing, and field returns to identify failure mechanisms and trends for yield and reliability optimization.
Develop and implement physics-based statistical Quality and Reliability models (e.g., ELF, TDDB, NBTI) to predict device failure mechanisms and lifetime behaviors.

Required SOC Quality and Reliability Engineer, Cloud
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
Our data centers are the most advanced in the world. In this role, you will help build the state-of-the-art SoCs that power these data centers by driving quality and reliability processes from the Integrated Circuit perspective. You will have an opportunity to create silicon and follow it into the field and back to drive improvements for the next-generations of chips.
You will have an understanding of Integrated Circuit (IC) flows, wafer processing, testing, qualification, yield, reliability, and failure analysis is expected. You will work with various cross-functional teams to develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute and test plans. You will collaborate with global hardware quality and reliability teams, silicon design, validation and engineering teams.
The AI and Infrastructure team is redefining whats possible. We empower customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity.
We're the driving force behind our 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 Cloud, Global Networking, Data Center operations, systems research, and much more.
Responsibilities
Lead the strategic definition and development of Design-for-Reliability (DfR) guidelines, collaborating with cross-functional subject matter experts to integrate reliability into early design stages.
Establish and direct the development of qualification hardware and test methodologies, managing internal teams and external vendors to ensure silicon and package verification.
Execute comprehensive silicon and package qualification programs (including high-temperature operating life (HTOL), early life failure rate (ELFR), electrostatic discharge and latch-up (ESD/LU), and biased highly accelerated stress test (b/HAST)) and conduct in-depth failure analysis to resolve quality issues.

Required SOC Quality and Reliability Engineer, Cloud
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
Our data centers are the most advanced in the world. In this role, you will help build the SoCs that power these data centers by driving quality and reliability processes from the integrated circuit perspective. You will create silicon and follow it into the field (and back) to drive improvements for the next generations of chips.
You will have an understanding of IC flows, wafer processing, testing, qualification, yield, reliability, and failure analysis. You will work with various cross functional teams to develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute and test plans. Within the larger organization you will collaborate with global hardware quality and reliability teams, silicon design, validation and engineering teams.

Responsibilities
Drive the strategic definition and development of design-for-reliability (DfR) guidelines, collaborating with cross-functional subject matter experts to integrate reliability into early design stages.
Define and lead the development of qualification hardware and test methodologies, managing internal teams and external vendors to ensure silicon and package verification.
Execute comprehensive silicon and package qualification programs (including high-temperature operating life (HTOL), early life failure rate (ELFR), electrostatic discharge/latch-up (ESD/LU), biased highly accelerated stress test (b/HAST), etc.) and conduct failure analysis to resolve quality issues.
Extract and analyze data from qualification programs, high-volume manufacturing, and field returns to identify failure mechanisms and trends for yield and reliability optimization.
Develop and implement physics-based statistical Quality and Reliability models (e.g., ELF, time-dependent dielectric breakdown (TDDB), negative bias temperature instability (NBTI) to predict device failure mechanisms and lifetime behaviors.