5+ years in product engineering, product development, manufacturing, or validation of PCBs, silicon, or complex systems experience.
History of leading complex GPU or board-level projects to mass production on schedule, with high quality and yield.
Ability to diagnose and resolve multi-disciplinary problems spanning silicon, board, firmware, and system layers.
Clear understanding of testing strategy economics - how coverage, test-time, and escape rate relate to yield and cost outcomes.
Communicates complex technical data clearly to both engineering and business audiences.
Travel Requirement: Willingness to travel up to 15%, both domestically and internationally.
Bachelor's degree in Electrical Engineering or Master's degree in Electrical Engineering, or equivalent experience.
Ways to stand out from the crowd:
Python or scripting experience applied to manufacturing analytics, test automation, or data pipelines.
Background coordinating cross-functional debug efforts across silicon, board, and systems.
Familiarity with HPC and hyperscale datacenter requirements - hardware engineering, power, cooling, reliability, and serviceability.
Experience qualifying advanced memory solutions (HBM, LPDDR) or high-speed SerDes interfaces.
Knowledge of PCBA manufacturing processes, mechanical tolerances, and system-level assembly constraints.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 212,750 USD for Level 3, and 168,000 USD - 258,750 USD for Level 4. You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until June 7, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
Additional Information
We build the hardware that runs the world's AI - and our Operations NPI team is how we bring it from silicon to data center at scale. At NVIDIA, we're proud to work on GPU platforms like Blackwell and Vera Rubin that push the boundaries of what's possible in compute. We move fast, we care deeply about quality, and we invest in people who want to grow across disciplines - board design, test engineering, yield analytics, and global manufacturing, often within a single program cycle. If you're energized by complex hardware challenges and want to see your work running inside the world's most powerful AI infrastructure, we'd love to talk.
Nvidia · Santa Clara, CA