Six Figure Work

Test Methodology Engineer

NVIDIA

Company websitenvidia.com (NVIDIA, opens in new tab)

Base salary $100K  to $207K

Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA

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  • LocationSanta Clara, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (32 min ago) · observed since

About this job

We are looking for a creative and experienced ATE Test Engineer. NVIDIA has continuously reinvented itself over three decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing — with the GPU acting as the brains of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and build our teams with the smartest people in the world. Join us at the forefront of technological advancement.

We need a creative individual who will help transfer GPU gaming and compute products from design engineering to mass production. You will be exposed to various aspects of building and testing NVIDIA products, from GPUs to assembled boards. In addition, your responsibilities will include working with overseas manufacturing teams to increase yields, test coverage and capacity, and reduce production costs. If you are passionate about building the highest quality server products that will change the world, then we really want to hear from you.

What you'll be doing:

  • Define, develop, implement, and support ATE test program solutions for the next generation of GPUs and AI server products.

  • ATE test method code development and debugging

  • Scripting and automation tools development and debugging

  • Actively participate in cross function team including Product Development Engineering, DFT, and IC design to efficiently debug any product failures and implement optimal solutions

What we need to see:

  • Completion of bachelor's degree or higher in Electrical Engineering/Computer Engineering (or equivalent experience).

  • 3+ years of relevant work experience in the semiconductor industry.

  • Knowledge of silicon verification, testing and manufacturing

  • Have knowledge in Advantest 93K ATE platform is essential

  • Experienced with Linux, and programming languages such as C/C++/Java and/or Perl/Python

  • Good communication skills and works well in a group environment and with cross functional teams that spans across continents

  • Experience with SRAM testing and familiarity with 2.5D or MCM assembly

  • Understanding of DFT insertion techniques including SCAN, ATPG, MBIST and IOBIST

  • Knowledge of system level testing/validation is a plus

  • Utilizing the AI in ATE testing is a plus and make you standout.

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
100,000 USD – 166,750 USD for Level 2; and 132,000 USD – 207,000 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

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.

Source: NVIDIA on Workday · View original posting (opens in new tab)

This range next to 6 other live NVIDIA roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live NVIDIA roles with the nearest advertised base floor
RolePublished base
Test Methodology Engineer (this listing)$100K - $207K
ASIC Verification Engineer, Memory Management - New College Grad 2027$100,000 - $189,750
Low Power ASIC Engineer - New College Grad 2027$100,000 - $189,750
ASIC Verification Engineer - New College Grad 2027$100,000 - $189,750
High Speed SerDes Validation Engineer - New College Grad 2026$100,000 - $189,750
Formal Verification Engineer - New College Grad 2027$100,000 - $189,750
GPU Verification Engineer - New College Grad 2026$100,000 - $189,750

Same $100K to $400K scale as every card. All NVIDIA roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-30
Where this pay comes from

Location as the employer wrote it: US, CA, Santa Clara (Levels 2-3 combined)

100,000 USD – 166,750 USD for Level 2; and 132,000 USD – 207,000 USD for Level 3.

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.