Role at a glance
- Salary
- $168K – $258.8K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years of work experience.
- Education
- BS degree in electrical engineering or equivalent experience.
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Role Summary
The Product Development Engineer will join NVIDIA’s Operations Product Development Engineering GPU Team to productize chips for consumer, professional, and datacenter markets. The role focuses on failure analysis, test-result correlation, testability improvements, manufacturing fallout reduction, and data-driven identification of yield and customer-quality risks.
What You'll Do
- Lead failure analysis of ATE-related escapes, including system-level and customer RMA failures, and drive corrective actions into wafer...
- Identify discrepancies between ATE, SLT, and BLT results and define guard bands, screens, correlation metrics, and test methodology changes.
- Partner with Design, DFX, Test Engineering, Hardware, PQE, and SQE teams to identify coverage gaps and influence chip-level testability...
- Drive cross-functional forums tracking end-to-end manufacturing fallout with ownership, closure criteria, and reduction targets.
- Define and build AI- and data-analytics-driven workflows to identify yield limiters, fallout signatures, systematic escapes, and early...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
BS degree in electrical engineering or equivalent experience; 8+ years of work experience; experience with product verification and failure analysis on Verigy 93K tester; proficiency in Python, C or C++, and statistical modeling using JMP or other data-analysis tools; solid communication, presentation, and interpersonal skills; track record as a strong collaborator.
Required
- BS degree in electrical engineering or equivalent experience
- 8+ years of work experience
- Experience with product verification and failure analysis on Verigy 93K tester
- Proficiency in Python, C or C++
- Statistical modeling of data using JMP software or other tools for data analysis
- Solid communication and presentation skills
- Solid interpersonal skills and track record as a strong collaborator
Preferred
- Direct working experience on using AI platforms for data analytics (Claude, cursor, lovable etc..)
- Direct working experience on improving system and board level yields by enhancing ATE structural test coverage
- A 'got-getter, can get it done' attitude and independent ‘out-of-box’ thinking.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
- Solid communication and presentation skills.
- Solid interpersonal skills and track record as a strong collaborator.
- Dedicated and able to work with minimum supervision.
Ways To Stand Out From Crowd
- Direct working experience on using AI platforms for data analytics (Claude, cursor, lovable etc..)
- Direct working experience on improving system and board level yields by enhancing ATE structural test coverage.
- A 'got-getter, can get it done' attitude and independent ‘out-of-box’ thinking’.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking, resilient, and hardworking people in the world. If you are learner, creative and collaborative, we want to hear from you!
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.