N

NVIDIA

Designs GPUs and AI HPC platforms

Product Development Engineer - Post-Si Characterization

Full-Time
$136k - $258.8k/yr+ Equity
Senior
Bachelor's, Master's
Santa Clara, CA, USA
In Person
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • A Bachelor or Master's degree in Electrical Engineering or equivalent experience.
  • At least 5 years of product development engineering or relevant experience.
  • Attention to detail, strong problem-solving skills, data-driven decision-making, critical thinking, and a solution-focused approach.
  • Experience with digital design, circuit analysis, characterization, and qualification.
  • Knowledge of automatic test equipment test flows, design for test, and device physics.
  • Proficiency in statistical data analysis using JMP software or other analytic tools.
  • Strong interpersonal communication skills and cross-functional collaboration.
  • Ability to define and drive problems to closure independently with minimal supervision.
Responsibilities
  • Drive the latest architecture designs to market as an integral part of product engineering.
  • Develop automatic test equipment test methodologies for next-generation GPU circuits, advanced silicon technologies, and innovative assembly processes.
  • Partner directly with feature designers to build success criteria from concept to silicon.
  • Identify and resolve yield bottlenecks and analyze and drive test failures at wafer and package level on automatic test equipment.
  • Propose design of experiments and develop solutions to complex characterization problems.
  • Lead cross-functional efforts with foundry, design for test, test, planning, and quality teams to root-cause and solve technical problems.
  • Influence next-generation ASIC designs and silicon solutions by improving circuit quality and testability at the architecture level to accelerate qualification, reduce test times, and deliver silicon releases.
Desired Qualifications
  • Hands-on experience with the Advantest 93K tester using SMT7 or SMT8 operating systems.
  • Knowledge of test-time and defects-per-million-opportunities reduction.
  • Experience with logic or static random-access memory and voltage/frequency characterization.
  • A design-for-test background and familiarity with automatic test equipment principles.
  • Examples of creative solutions to silicon or package problems and familiarity with automation or artificial intelligence tools.

About the company

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify's Take

What believers are saying

  • OpenAI's GPT-6 Astra Ultrafast runs on Blackwell, validating NVIDIA's inference leadership.
  • September 2026 added a $150 billion buyback, signaling relentless cash generation.
  • Meta's multiyear Blackwell-Rubin partnership expands NVIDIA deployments across cloud and on-premises systems.

What critics are saying

  • DeepSeek-Huawei TileLang targets CUDA, and China's ecosystem split deepens in 2026.
  • NVIDIA guides zero China data-center revenue, leaving geopolitical access permanently broken.
  • FTC liability skepticism and Connecticut enforcement expose NVIDIA customers to agent-related lawsuits.

What makes NVIDIA unique

  • CUDA locks 7.5 million developers into NVIDIA's software stack and tooling moat.
  • Blackwell and Rubin keep NVIDIA first on inference performance and deployment cadence.
  • Networking plus BlueField and NVLink turn chips into full AI infrastructure platforms.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

↑ 0%

1 year growth

↓ -1%

2 year growth

↓ -2%
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