System Verification Co-Design Engineer — Speed and Reliability
NVIDIAJob Title
System Verification Co-Design Engineer — Speed and Reliability
Role Summary
Work on system-level speed and reliability features for NVIDIA silicon: develop verification collateral and automation to characterize and validate features, and lead debug of complex silicon issues to meet program schedules.
Hands-on engineering role that combines system verification, automation, and AI-assisted workflows to compress characterization and debug cycles.
Experience Level
Mid-level — requires approximately 4+ years of related hardware engineering experience.
Responsibilities
Primary responsibilities include:
- Collaborate with architects, hardware, firmware/software, reliability, and operations to co-design system-level speed features.
- Analyze system behavior, speed/reliability margins, and constraints to propose optimizations.
- Translate hardware and architecture requirements into verification techniques for pre- and post-silicon flows.
- Perform closed-loop validation by correlating silicon behavior with timing simulation and design expectations; provide actionable feedback.
- Define and refine pre- and post-silicon bring-up flows to ensure product quality, performance, and schedule efficiency.
- Design and implement automation for system speed modeling; apply AI/LLM-assisted workflows (log analysis, pattern detection, scripting acceleration) to accelerate characterization and debug.
- Lead debug of complex silicon and system-level issues, including critical defects that affect shipment schedules.
Requirements
Must-have skills and experience:
- 4+ years in hardware engineering roles involving silicon bring-up, frequency and power characterization, and PPA analysis.
- Hands-on experience with pre- and post-silicon phases, tester-to-system correlation, and lab instrumentation (oscilloscopes, multimeters, DAQs).
- Scripting proficiency in Python and/or Perl; comfortable in Windows, Linux, and Android environments.
- Familiarity with statistical methods and data-analysis tools (e.g., JMP) and strong data-driven judgment.
- Demonstrated use of AI or LLM-based tools in engineering workflows, with awareness of output validation and automation risks.
- Strong cross-functional communication and debugging skills for complex silicon/system problems.
Education Requirements
MS in Electrical Engineering, Computer Engineering, Systems Engineering, or equivalent practical experience; the posting explicitly allows equivalent experience in lieu of the degree.
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.
