Senior Silicon Validation Methodology Engineer - Low Power
NVIDIA is hiring a Senior Silicon Validation Methodology Engineer - Low Power in Shanghai, China. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Python, C and silicon validation.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
- The role was posted within the past two weeks.
AI in this role
Lead low-power silicon validation methodology, incorporating AI-enabled analysis to optimize GPU, SoC, and CPU performance.
NVIDIA Silicon Co-Design Group (SCG) is a wide-ranging, multi-functional team at NVIDIA. We sit at the crossroads of design, architecture, marketing, operations, and productization. Our contributions span from the architecture stage through final product definition. We architect solutions for Datacenter, Server, Gaming, Robotics, Automotive, and Embedded markets. We are fast-paced, collaborative, and focused on making groundbreaking, impactful products. We are seeking a Senior Silicon Validation Methodology Engineer for Low-Power (LPWR). You will own the department LPWR validation methodology across GPU, SoC, and CPU, from architecture to silicon to product.
What you'll be doing:
- Own architecture, design, and first-use of end-to-end LPWR validation methodology from silicon to product, covering corners, edge conditions, variability, and real-world scenarios. Set the department standard for LPWR validation so it is reused across a broad array of silicon products.
- Define what needs to be tested, why, and how — including coverage bounds, PVT/variability, test-time vs. schedule, signoff criteria, milestone playbooks, and SOL(speed of light) expectations.
- Invent and land new LPWR validation approaches that go beyond extending an existing test plan. Challenge current paradigms on performance, power, idle vs. active behavior, and corner-case coverage, and drive the resulting methods, tools, and metrics into org default practice.
- Set LPWR validation strategy and policy across teams, including long-lead items that outlive a single execution cycle. Translate architecture and product goals into multi-generation methodology, infrastructure, and tool investments.
- Drive cross-functional consensus with Architecture, Design, Firmware, and Software under conflicting PPA, coverage, latency, and schedule priorities.
- Improve validation workflow at department scale by building and adopting automation, coverage metrics, pre-silicon to post-silicon correlation, and AI-enabled analysis. Fold learnings back into methodology, spec, and design.
What we need to see:
- A Master's or Bachelor's degree in Electrical Engineering, Computer Engineering, or equivalent experience.
- 8+ years of hands-on silicon validation methodology experience, with deep ownership of low-power architecture and design (idle power, power gating, clocking, DVFS, and related features) and silicon features tied to current energy-efficient design.
- Proven record of creating new LPWR validation methods, tools, or signoff criteria that were adopted across multiple products or teams.
- Expert debug of silicon LPWR issues, and the ability to deconstruct ambiguous failures into simpler, reusable validation and corrective approaches that raise quality and efficiency for the org.
- Demonstrated strong ability to set validation strategy under hard trade-offs: functionality vs. performance/power, latency vs. coverage, and coverage vs. schedule.
- Strong collaboration skills and Proven track record of influencing and leading cross-functional/group(design, Board, FW, SW) consensus through product launches in low-power domains.
- Strong AI-enabled skills and thinking — use AI to accelerate analysis, exploration, and documentation while maintaining rigor, originality, and judgment that do not come from AI.
Ways to stand out from the crowd:
- Set LPWR or power-management validation policy, playbooks, or signoff bars that other teams ran without you in the critical path.
- Have shipped methodology reuse across multiple chips, SKUs, or platforms, with measurable impact such as higher coverage, fewer debug loops, lower SOL, or faster bring-up.
If you are energized by owning a domain, setting the bar for others, and turning low-power silicon expertise into reusable methodology at NVIDIA scale, we'd love to talk to you.
How we rate this
Senior Silicon Validation Methodology Engineer - Low Power at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where silicon validation was part of your work. What did you do?
- Tell me about a project where low power architecture was part of your work. What did you do?
- Tell me about a project where dvfs was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
- Tell me about a project where hardware testing was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Silicon Validation, Low Power Architecture, Dvfs, Automation, and Hardware Testing. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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