NVIDIA
Senior System Integration and Validation Engineer
$168K–$310K
US, CA, Santa Clara · Senior · Full-time · Posted Sep 23, 2026
- Experience
- 8+ years of post-silicon validation, system integration, or platform debug experience on shipped GPU, CPU, or SoC products.
- Education
- BTech/BE or MTech/ME in Electronics, Electrical, or Computer Engineering (or equivalent experience).
About the job
Leads system validation, cross-stack debug, and AI-enabled validation workflows for NVIDIA GPU, SoC, and platform programs, helping identify and resolve issues before product release.
What you'll do
- Own end-to-end system validation, including feature checks, PVT stress, system-stress campaigns, and multi-unit fleet testing.
- Lead complex silicon, board, and software debug through root-cause analysis and productized fixes; coordinate cross-functional crisis response.
- Develop automated test coverage and deploy guarded AI-enabled debug and validation workflows with measurable impact.
What they ask for
- BTech/BE or MTech/ME in Electronics, Electrical, or Computer Engineering, or equivalent experience.
- 8+ years of post-silicon validation, system integration, or platform debug experience on shipped GPU, CPU, or SoC products.
- Hands-on debug across silicon, board, and software boundaries, including logic design, signal integrity, power delivery, high-speed I/O, and PVT behavior.
- Demonstrated leadership in resolving ambiguous multi-team failures and building or scaling AI-driven validation workflows with adoption and measurable impact.
Nice to have
- Reusable validation methodologies, debug playbooks, or test frameworks adopted by other teams, supported by recognized contributions.
- Subsystem depth in HBM, SerDes or high-speed I/O, power and thermal, or advanced packaging; or experience partnering across global engineering hubs.
Pay
168,000 USD - 264,500 USD (base salary, Level 4); 196,000 USD - 310,500 USD (base salary, Level 5)
Tools
GPU, SoC, PVT, HBM, SerDes, RAG
AI focus
Build and deploy AI-enabled debug, triage, root-cause hypothesis generation, and regression workflows with evaluations, guardrails, and measurable team-level impact.
Model-written summary · the original posting is authoritative