NVIDIA
Technology
ProductDevelopmentEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“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.
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
Applying for this Product Development Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about NVIDIA?
Real rants from real employees. Read before you apply.