NVIDIA

Technology

ProductDevelopmentEngineer

$168–259k Santa Clara, California, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Product Development Engineer at NVIDIA. Skills: Failure analysis, Data analytics, ATE testing. Lead failure analysis of ATE-related escapes. Determine root cause”

What You'll Achieve.

Reduce downstream fallout; Improve testability; Improve outgoing quality; Measurable reduction targets

Industry & Context.

Technology
Problems you'll solve

Creative problem solvers; Failure analysis; Root cause analysis; Identify discrepancies; Identify gaps; Identify limiters; Identify signatures; Identify escapes; Identify indicators

What They're Looking For.

Must Have

BS degree in electrical engineering, 8+ years of work experience, Experience with product verification, Experience with failure analysis on Verigy 93K tester, data engineering skillset, proficiency in Python, proficiency in C, proficiency in C++, statistical modeling of data using JMP software, Solid communication skills, Solid presentation skills, Solid interpersonal skills, track record as a collaborator, Dedicated, able to work with minimum supervision

Nice to Have

Direct working experience on using AI platforms for data analytics, Direct working experience on improving system and board level yields, enhancing ATE structural test coverage, A 'got-getter, can get it done' attitude, independent ‘out-of-box’ thinking

What You'll Do.

Lead failure analysis of ATE-related escapes

Drive corrective actions back into wafer sort

Drive corrective actions back into package test

Identify systematic discrepancies between ATE

Identify systematic discrepancies between SLT

Identify systematic discrepancies between BLT

Define correlation metrics

Define test methodology changes

Reduce downstream fallout

Partner with Design teams

Partner with DFX teams

Partner with Test Engineering teams

Partner with Hardware teams

Partner with PQE teams

Partner with SQE teams

Identify DFx coverage gaps

Identify ATE coverage gaps

Influence chip-level hooks

Influence observability features

Improve outgoing quality

Drive cross-functional forums

Track end-to-end fallout across NVIDIA manufacturing

Define clear ownership

Define closure criteria

Define measurable reduction targets

Define AI-driven workflows

Build AI-driven workflows

Define data-analytics-driven workflows

Build data-analytics-driven workflows

Identify yield limiters

Identify fallout signatures

Identify systematic escapes

Identify early indicators of customer-quality risk

How You'll Work.

Team & Collaboration

Partner with Design; Partner with DFX; Partner with Test Engineering; Partner with Hardware; Partner with PQE; Partner with SQE; Cross-functional forums

Communication Scope

Solid communication; Solid presentation

Full Job Description

As one of the technology industry's most desirable employers, NVIDIA is an industry leader in high performance computing, gaming and AI. NVIDIA's GPUs are extraordinary in performance and efficiency, and we are continually innovating creative ways to deliver outstanding solutions in a wide range of sectors. We are seeking Product Development Engineers who are experienced, creative problem solvers in various areas and passionate to want to make a visible impact with the work they do. As part of the Operations Product Development Engineering GPU Team, you will work on productizing NVIDIA’s chips into consumer, professional and datacenter markets. **What you’ll be doing:** * Lead failure analysis of ATE-related escapes – specifically failures seen at system-level and customer RMAs. Determine root cause and drive corrective actions back into wafer sort and package test. * Identify systematic discrepancies between ATE, SLT and BLT results; define guard bands, screens, correlation metrics, and test methodology changes to reduce downstream fallout. * Partner with Design, DFX, Test Engineering, Hardware, PQE, and SQE teams to identify DFx and ATE coverage gaps, then influence chip-level hooks, test modes, monitors, and observability features that improve testability and outgoing quality. * Drive cross-functional forums to track end-to-end fallout across NVIDIA manufacturing, with clear ownership, closure criteria, and measurable reduction targets. * Define and build AI / data-analytics-driven workflows to identify yield limiters, fallout signatures, systematic escapes, and early indicators of customer-quality risk. **What We Need To See:** * BS degree in electrical engineering or equivalent experience. * 8+ years of work experience. * Experience with product verification and failure analysis on Verigy 93K tester. * Strong data engineering skillset, with proficiency in Python, C or C++, and statistical modeling of data using JMP software or other tools for data analysis * So

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