Unknown Company
Senior Silicon Validation Engineer, Volume Production and Yield
Google welcomes people with disabilities.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New Taipei, Banqiao District, New Taipei City, Taiwan; Zhubei, Zhubei City, Hsinchu County, Taiwan.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New Taipei, Banqiao District, New Taipei City, Taiwan; Zhubei, Zhubei City, Hsinchu County, Taiwan.
Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
- 8 years of experience in silicon development, including post-silicon validation, product engineering, test engineering, or yield analysis.
- Experience leading a technical project or sub-team.
- Experience with embedded systems, firmware, or core software development environments (e.g., C, Python).
- Experience with semiconductor manufacturing methodologies, silicon test processes (e.g., ATE, SLT), and fault isolation techniques.
Preferred qualifications:
- Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
- Experience with delivering technical impact to launch silicon products into high volume manufacturing pipelines.
- Experience with the failure analysis and debug of complex Systems on Chip (SoCs).
- Experience with a broad range of compute platforms and SoCs (e.g., dedicated mobile or specialized AI processors).
- Experience applying AI/ML models, statistical methods, and data analysis for silicon yield optimization.
- Excellent problem-solving, people management, and written and verbal communication skills.
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google'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.
We are seeking a highly motivated and experienced Silicon Engineer to drive our Volume Production and Yield efforts.
In this pivotal role, you will be the primary technical owner for the transition of our silicon designs into high-volume factory manufacturing, delivering screening packages to factory partners and driving continuous silicon yield monitoring, failure analysis, voltage margin characterization, and improvement across the product lifecycle. You will leverage AI-driven data analytics and machine learning techniques to optimize yield, accelerate failure debug, and enhance overall silicon quality.
Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.
Responsibilities
- Provide technical guidance and expertise for volume productization and post-silicon yield enhancement. Define and deliver silicon screening packages to factory organizations.
- Execute and refine the silicon yield management strategy, leading failure analysis, root cause debug of limiters, and production data analysis. Leverage AI/ML tools to automate yield analysis and streamline failure debug.
- Engage with cross-functional partners (SiVal, Design, DV, PDTE, Operations, external factory teams) to meet stringent yield goals and resolve critical manufacturing challenges.
- Establish processes for screening package releases, data acquisition, and failure analysis protocols. Proactively identify risks and key opportunities for yield across the product lifecycle, from NPI through mass production.
- Communicate technical status, risks, and solutions clearly to cross-functional stakeholders and engineering leadership.