Circuit Validation Engineer(NCG)

We are seeking a Circuit Validation Engineer(NCG) to join our Silicon Co-Design Group (SCG) team at NVIDIA. As a Circuit Validation Engineer, you will play a critical role in defining and validating circuit methodologies across GPUs and SoCs, ensuring they meet our high-quality standards.

Job Summary: You will be responsible for standing up silicon co-design prototypes and measurement setups, planning and executing design of experiments (DOE), building Python pipelines and analyses, and partnering with cross-functional teams to add debug hooks and iterate on prototypes.

Key Responsibilities:

• Standing up silicon co-design prototypes and measurement setups to expose power-rail noise, circuit enablement and tuning, performance, and volume behavior.
• Planning and executing design of experiments (DOE) to analyze main effects and interactions.
• Building Python pipelines and analyses to turn prototype, DOE, simulation, and characterization data into traces, summaries, and inputs for firmware tuning, product specs, and manufacturing limits.
• Partnering with architecture, design, validation, and firmware teams to add debug hooks, iterate on prototypes, and document findings.
• Using secure, traceable, validated AI-assisted workflows for experiment planning, analysis, and documentation.

Requirements:

• MS in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Background in a related silicon, validation, characterization, productization (SoC, GPU, CPU, or similar).
• Working knowledge of silicon circuit/clock/power/noise concepts, such as DVFS, Vmin/Fmax, shmoo, PDN/noise, Driver, or margins.
• Hands-on experience with lab or post-silicon bring-up, experiment or characterization campaigns, or manufacturing test/limits that consume chip data.
• Proficiency in Python (or similar) for data analysis, automation, and validation; comfort with Git and structured test/regression.
• Ability to turn an ambiguous silicon question into a measurable experiment, communicate clearly across teams, and write notes others can execute from.
• Strong AI-enabled skills and thinking.

Nice to Have:

• Experience running a test-chip, prototype vehicle, or characterization DOE.
• Direct experience on GPU/SoC/CPU circuits, power, performance, PDN/noise, or sim-to-silicon correlation.
• Shipped an internal tool, dashboard, or data pipeline (Python, databases, web apps) that other people use.
• Hands-on experience with large language models (LLMs) in an engineering workflow.
• Exposure to firmware/BIOS parameters, eFuse/limits, or ATE/SLT screening, and how they connect to product SKUs.