Silicon Product Engineer – Manufacturing
NVIDIAJob Title
Silicon Product Engineer – Manufacturing
Role Summary
Join NVIDIA's Testability, Manufacturability, Reliability & Quality (TMRQ) team to validate and implement SLT/BLT production diagnostics and test specifications for complex silicon (GPUs, SoCs, CPUs) from first power-on through high-volume manufacturing (HVM).
The role focuses on post-silicon validation, production correlation, and test flow development across hardware, software, and production operations to deliver quality, yield, and efficient manufacturing at scale.
Experience Level
Mid-level. The role requests approximately 3+ years of relevant industry experience in post-silicon PVT validation and/or high-volume manufacturing testing.
Responsibilities
Primary responsibilities include validating production diagnostics and defining effective SLT/BLT test coverage for high-volume screens, and improving manufacturing workflows through data-driven analysis.
- Develop and implement closed-loop analysis for VF characteristics and POR expectations versus production screens.
- Support VF/VMIN/VMAX/PVT specification validation and productization across Manufacturing teams.
- Collaborate with silicon PVT, IO, system feature, and production teams to determine SLT/BLT test conditions, content, and flows.
- Prototype and tune speed, power, circuits, yield, and quality for effective SLT socketed coverage.
- Maintain SLT/BLT test flows and correlate production testing data with silicon characterization and diagnostics.
- Drive process improvements and preventative actions via root cause analysis and data analytics.
- Partner with software and platform teams to improve SLT testing infrastructure, debug controls, and data collection.
Requirements
Must-have technical skills and experience; separates notable extras as nice-to-have.
- Must-have: 3+ years of industry experience in post-silicon PVT validation and/or HVM testing for complex SoCs/GPUs/CPUs.
- Must-have: Hands-on lab experience with silicon bring-up, lab debug, shmoo analysis, VF characteristics, test content bring-up, and correlation to Si characterization and yield.
- Must-have: Strong electrical engineering fundamentals, device physics knowledge, and familiarity with silicon design, STA concepts, fault analysis, and sampling.
- Must-have: Strong data analysis skills and experience working with large volumes of data; use of analytics to drive manufacturing decisions.
- Must-have: Experience with Python, BASH, Linux, and scripting for test and data workflows.
- Good understanding of firmware/driver interactions with hardware and manufacturing test strategy from planning through ramp to production.
- Nice-to-have: Prior exposure to GPUs, CPUs, AI accelerators, or other large-scale SoCs in HVM environments and experience applying AI tools to testing/debug workflows.
Education Requirements
Bachelor's or Master’s degree (or equivalent) in Microelectronics, Electrical, Electronic, Computer Engineering, or a closely related field - or equivalent practical experience.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
