We are looking for a creative and independent Test Engineer with hands-on experience in digital test content development (ATPG, LBIST, MBIST).Our high-speed networking products are industry leaders, continually redefining speed, bandwidth, and reliability across generations.
In this role, you will be responsible for developing, validating, and supporting digital test content for NVIDIA’s advanced Network Silicon ICs (Switches, NICs, SmartNICs). You will work closely with DFT, design, and test engineering teams to ensure high-quality and scalable test content from wafer to final product.
What you'll be doing:
Develop ATPG, LBIST, and MBIST content based on DFT architecture
Run validation flows (simulation/emulation/silicon), analyze failures, and debug pattern issues
Collaborate with DFT teams to ensure alignment between test logic and content implementation
Support test program bring-up and pattern integration on production testers
Continuously improve coverage, pattern quality, and pattern generation efficiency
Work with product and test engineering to support yield improvement and debug activities
What we need to see:
B.Sc. in Electrical Engineering
Strong understanding of scan, ATPG, BIST (MBIST/LBIST), and DFT concepts
3 years of experience in digital test content development or related roles
Scripting skills (Python/TCL/Perl) – an advantage
Strong analytical and debug skills, independent and detail-oriented
Ways to stand out from the crowd:
Familiarity with ATE test environments (e.g., UltraFlex)
Experience with silicon validation and failure analysis
Knowledge in STA, RTL simulation, or gate-level netlist analysis
NVIDIA has some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. We are committed to fostering a diverse 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.
Skills Required
- B.Sc. in Electrical Engineering
- Strong understanding of scan, ATPG, BIST (MBIST/LBIST), and DFT concepts
- 3 years of experience in digital test content development or related roles
- Scripting skills (Python/TCL/Perl)
- Strong analytical and debug skills; independent and detail-oriented
- Familiarity with ATE test environments (e.g., UltraFlex)
- Experience with silicon validation and failure analysis
- Knowledge in STA, RTL simulation, or gate-level netlist analysis
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
