N

NVIDIA

Designs the chips and software that power AI

Product Development Engineer

Full-TimeUpdated on 10/15/2026
No salary listed
Mid
Master's
Hsinchu, Hsinchu City, Taiwan
In Person
Hardware EngineeringHardware Validation & Testing

About the job

Requirements
  • A Master’s degree or higher in Electrical Engineering, Computer Engineering, or Physics, with at least two years of experience.
  • Experience in post-silicon characterization, correlation, qualification (including High-Temperature Operating Life testing), and debug.
  • Knowledge of automatic test equipment testing, design-for-test methodology, and complementary metal-oxide-semiconductor device physics.
  • Familiarity with central processing unit architecture fundamentals, such as cache hierarchies, coherency fabrics, and multi-core power management, or automotive high-reliability product lifecycles.
Responsibilities
  • Architect, design, and implement efficient manufacturing test processes for new central processing unit and Automotive system-on-chip products.
  • Identify and implement test processes to improve manufacturing efficiency and test coverage for central processing unit architectures and automotive chips built using leading-edge process technology.
  • Analyze product yield limiters, drive minimum operating voltage and maximum frequency optimization through speed binning, and resolve failures on automatic test equipment while leading cross-functional efforts with design, foundry, quality, and test teams to identify root causes and implement improvements.
  • Define product test requirements and drive new product introduction bring-up, validation, characterization, and reliability qualification, such as AEC-Q100, to support production ramps at worldwide manufacturing sites.
  • Influence and optimize the placement of test coverage across the test and supply chain to meet automotive zero-defect screening requirements and reduce cost.
  • Lead detailed data analysis to correlate field and customer failures with internal production data to understand root cause, risk, and exposure.
Desired Qualifications
  • Understanding of design-for-test insertion techniques, including scan, automatic test pattern generation, memory built-in self-test, and logic built-in self-test for functional safety and in-field testing.
  • Good understanding of automotive semiconductor quality standards, including AEC-Q100 qualification pathways and ISO 26262 functional safety guidelines.
  • Familiarity with JMP data analytics tools and Python, Java, or another scripting language for large-scale test data evaluation and screening limits, such as part average analysis.
  • Experience with automatic test equipment test programs, test systems, and hardware such as 93K and uFlex for complex system-on-chip and central processing unit bring-up and debug, and use of failure diagnosis and isolation tools to identify and resolve silicon manufacturing defects.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

Company Equity

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Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

-2%
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