System Verification Co-Design Engineer — Speed and Reliability

Job Title

System Verification Co-Design Engineer — Speed and Reliability

Role Summary

Work on system-level speed and reliability features for GPU platforms, developing verification collateral, automation infrastructure, and leading debug of silicon issues to meet delivery schedules. The role is part of the SCG organization and requires cross-functional collaboration across architecture, hardware, firmware/software, process/reliability, and operations.

Hands-on engineering with modern tooling, including AI-assisted workflows, to compress characterization and debug cycles while maintaining technical rigor.

Experience Level

Mid-level — typically requires 4+ years of related hardware engineering experience.

Responsibilities

Primary responsibilities include system co-design, verification strategy, and post-silicon validation and debug.

• Collaborate with system architects and cross-functional teams to co-design system-level speed features.
• Analyze system behavior, speed and reliability margins, and bounding constraints to optimize margins.
• Translate hardware features and architectural requirements into verification techniques and coverage plans.
• Perform closed-loop validation by correlating silicon behavior with timing simulation and design expectations.
• Define, prototype, and refine pre- and post-silicon bring-up and validation flows.
• Design and implement automation tools for system speed modeling and characterization.
• Apply AI/LLM-assisted workflows for automated log analysis, pattern detection, and scripting acceleration where appropriate.
• Architect testability features for performance, power, and reliability with design, DFx, and ATE teams.
• Lead debug of complex silicon and system-level issues to enable on-time product shipment.

Requirements

Must-have technical skills and experience to perform the role.

• Hands-on experience with silicon bring-up, frequency and power characterization, and pre-/post-silicon PPA analysis.
• System/platform-level understanding, tester-to-system correlation, and experience with 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 (JMP or equivalent).
• Demonstrated use of AI or LLM tools in engineering workflows, with judgment about validation and automation risk.

Nice-to-have:

• Background in gaming, automotive, or datacenter segments.
• Experience building or deploying AI-assisted characterization, log analysis, or debug automation in production silicon environments.
• Familiarity with LLM evaluation, prompt engineering, or agentic scripting pipelines applied to silicon data analysis.

Education Requirements

MS in Electrical Engineering, Computer Engineering, Systems Engineering, 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.