> Markdown version of [/jobs/ext/2279878-system-speed-and-reliability-co-design-engineer](https://www.wearedevelopers.com/jobs/ext/2279878-system-speed-and-reliability-co-design-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # System Speed and Reliability Co-Design Engineer - **Company:** NVIDIA Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Experienced - **Salary:** $136,000.0 - $218,500.0 - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Artificial Intelligence, Data Analysis, Android Software Development, Systems Engineering, Computer Engineering, Data Centers, Software Debugging, Linux, Perl (Programming Language), Firmware, Python (Programming Language), Log Analysis, Pattern Recognition, Software Requirements Analysis, Scripting, JMP (Statistical Software), Large Language Models, Prompt Engineering, GPT - **Published:** August 28, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/System-Speed-and-Reliability-Co-Design-Engineer_JR2018911-1 ## About the Role * MS in EE, CE, Systems Engineering, or equivalent experience. * 4+ years of experience in a related hardware engineering role. * Hands-on experience with silicon bring-up, frequency and power characterization, PPA analysis in pre- and post-silicon phases, System/Platform level understanding, 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 (JMP or equivalent). * Demonstrated use of AI or LLM-based tools (e.g., Claude, Copilot, ChatGPT) in an engineering workflow-scripting acceleration, log triage, data analysis-with clear judgment about output validation and where automation introduces risk. Ways to stand out from the crowd: * Background in gaming, automotive, or datacenter segments. * Experience building or deploying AI-assisted characterization, log analysis, or debug automation workflows in a production silicon environment. * Familiarity with LLM evaluation, prompt engineering, or agentic scripting pipelines applied to silicon data analysis. ## Description SCG sits at the crossroads of design, architecture, marketing, and productization-owning the journey from the architecture stage through final product definition across Gaming, Datacenter, Automotive, and Embedded markets. As a Silicon Speed Features Engineer, you will co-design system-level speed features, build the validation and automation infrastructure to characterize them, and lead debug of the complex silicon issues that stand between a program and on-time shipment. This is a hands-on role for an engineer who combines deep technical craft with the drive to compress cycle time using modern tooling-including AI-without losing rigor. What You'll Be Doing: * Collaborate cross-functionally with system architects, hardware, firmware/software, process/reliability, and operations teams to co-design system-level speed features and deliver industry-defining products. * Define System level specifications, margins, bounding box constraints that satisfy design expectations and product quality. * Provide system requirements for hardware and features affecting speed and reliability, from pre-silicon through productization. * Translate hardware features and architectural requirements into validation techniques that achieve full coverage across testing flows. * Perform closed loop validation by correlating silicon behavior against timing simulation and design expectations; provide actionable feedback to improve future designs. * Define, prototype, and refine pre- and post-silicon bring-up flows to ensure product quality, performance, and schedule efficiency. * Design and implement automation tools for system speed modeling; apply AI and LLM-assisted workflows (e.g., automated log analysis, pattern detection, scripting acceleration) to compress characterization and debug cycles. * Architect and influence testability features critical to performance, power, and reliability in partnership with design, DFx, and ATE teams. * Lead debug of complex silicon and system-level issues, including show-stopper defects, to enable on-time product shipment. ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Playing Pong on a shoulder press machine](https://www.wearedevelopers.com/videos/100140-playing-pong-on-a-shoulder-press-machine) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Your Next AI Needs 10,000 GPUs. 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