AI Insights
NVIDIA

Lead Speed and Reliability Engineer - DFP

NVIDIA · Santa Clara, California, US
full-timelead (5-15 yrs)Posted 31d ago
Hardware / Silicon EngineeringIC4IC + ManagementHybrid (3d)
StackSTA timing closureCircuit designNoise characterizationProduct binningPerformance/power optimizationCPU/GPU/SOC NPI bringupSilicon bringup and tuningStatistical analysisSubstrate noise analysisPower supply noise analysisCUDAData analysis toolsTest plan developmentHardware characterization

Summary

NVIDIA's Silicon Solutions Group (SSG) is seeking a Lead Speed and Reliability Engineer for their Design for Productization (DFP) team. The role focuses on driving methodology and design for testing and deploying new hardware features related to speed, timing, and reliability across NVIDIA's full chip portfolio — from datacenter to consumer, automotive, and mobile.

About the role

NVIDIA is the industry leader in high-performance computing, gaming, and AI. Our GPUs and SOCs give outstanding performance and efficiency, revolutionizing myriad fields like cell research, robotics, crypto mining, and so many more. We revolutionized the AI world by inventing CUDA. And we are just getting started. Silicon Solutions Group (SSG) is a multifaceted, multi-functional team at NVIDIA. We sit at the crossroads of design, architecture, marketing, and productization. We architect and deliver innovative solutions for various markets like Gaming, Datacenters, Servers, Automotive, and Embedded. We are fast-paced, dynamic, share a sense of humor, and collaborate extensively to push the boundaries of what is possible. Design for Productization, DFP for short, is a group within SSG with a focus on SOL methodology, design, test plan, and tools to efficiently enable, test, and deploy new chip features. The group is multi-faceted, working across SSG and other partner teams, to enable efficient testing and deploy features at SOL quality and efficiency.

The DFP team is looking for a Speed and Reliability Lead. You will be leading and crafting testability features related to Speed, Timing, and Reliability from the ground up as you help turbocharge NVIDIA's chips into groundbreaking consumer, professional, server, mobile, and automotive solutions.

What you will be doing:

  • Driving methodology and design for NVIDIA testing and deploying new HW features. Crafting related tools and methods to ensure SOL, efficient testing meeting quality benchmarks. Scope spans from the datacenter to the chip level.

  • Creating productization processes and methodologies to guide SSG teams on templates to characterize, test, and release state-of-the-art products. Specify critical metrics to meet across the process and improve these based on findings.

  • Prototype and fine-tune these on pre-production silicon (including test chips) fabricated using innovative processes for speed, performance, power, yield, and quality.

  • Provide guidance to silicon-facing teams on how to take the feature to productization, including hands-on bringup for feature validation.

  • Collate takeaways from silicon and correlate to design. Provide feedback to improve the feature in the future, thus being responsible for the feature roadmap for all NVIDIA products.

  • Collaborating with the best minds in NVIDIA across various teams (System Architecture, Automation, PDE, Application Engineering, Product Manager, Sales, Operations) in a dynamic, creative work environment to bring industry-defining products to market.

What we need to see:

  • MS in EE, CE, Systems Engineering (or equivalent experience) and 5+ years of experience in a related hardware engineering position.

  • Previous engineering experience in CPU/GPU/SOC NPI bringup, with focus on driving methodologies and test plans. Familiarity with silicon bringup and tuning a plus, related to timing, speed, reliability and power.

  • Familiarity with STA timing closure, circuit design, noise characterization, product binning methods, and/or performance/power optimization techniques.

Ways to stand out from the crowd:

  • Familiarity with statistical methods and tools for data analysis

  • Background with substrate and power supply noise analysis and mitigation

  • A "go-getter, can get it done" attitude and independent 'out-of-the-box' thinking.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. If you're creative and ambitious, we want to hear from you!
 

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 27, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What you'll do

1Drive methodology and design for NVIDIA's testing and deployment of new HW features, spanning datacenter to chip level
2Craft related tools and methods to ensure SOL, efficient testing meeting quality benchmarks
3Create productization processes and methodologies to guide SSG teams on templates to characterize, test, and release products
4Specify critical metrics and improve them based on findings
5Prototype and fine-tune features on pre-production silicon (including test chips) for speed, performance, power, yield, and quality
6Provide guidance to silicon-facing teams on productization, including hands-on bringup for feature validation
7Collate takeaways from silicon, correlate to design, and provide feedback to improve the feature roadmap for all NVIDIA products
8Collaborate across teams including System Architecture, Automation, PDE, Application Engineering, Product Management, Sales, and Operations

Requirements

MS in EE, CE, or Systems Engineering with 5+ years of hardware engineering experience
Hands-on experience with CPU/GPU/SOC NPI bringup, including methodology and test plan development
Strong familiarity with STA timing closure, circuit design, noise characterization, and product binning
Experience crafting productization processes and methodologies for characterization, testing, and product release
Ability to correlate silicon takeaways with design and drive long-term feature roadmaps across NVIDIA product lines

Nice to have

Statistical methods and tools for data analysis
Substrate noise analysis and mitigation
Power supply noise analysis and mitigation
Independent/out-of-the-box thinking
Silicon tuning for timing, speed, reliability, and power

Role overview

Role family
Hardware / Silicon Engineering
Level
IC4 — embedded
Experience
5–15 years
Type
Hybrid (IC + Management)
Remote policy
Hybrid (3 days)
Visa sponsorship
Not offered

Tech stack analysis

TOOLS
STA toolsStatistical data analysis toolsSilicon characterization toolingAutomation frameworks

Green flags

6 items
Salary ranges explicitly disclosed for two levels (L3: $136K–$218.5K; L4: $168K–$264.5K), which is rare and candidate-friendlytransparency

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Benefits breakdown

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Hiring insights

JD quality
8/10
Urgency
medium
Autonomy
high
Team size
medium (5-15)

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Red flags

PRO3 items
Breadth of scope is very wide (datacenter to chip-level, consumer/professional/server/mobile/automotive) — may indicate resource constraints or expectation of superhero-level outputrequirements

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Interview insights

PRO
Rounds
5
Duration
4 wks
Difficulty
very hard
Take-home
Yes

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Career path

PRO
Next roles
Principal Speed & Reliability EngineerSenior Staff Silicon EngineeringEngineering Manager – DFP/SSG

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About the company

NVIDIA is the world's leading designer of GPUs and AI computing platforms. Its chips power everything from gaming and data centers to autonomous vehicles and scientific research. With a market cap exceeding $2 trillion, NVIDIA's CUDA platform and AI accelerators have become the backbone of the global AI revolution.

HQSanta Clara, CA, USA
Interview difficultyvery hard
Build vs Maintainbuild
Cross-functionalYes