Senior DFT Engineer

Posted 6 Hours Ago
Be an Early Applicant
2 Locations
Hybrid
168K-311K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Leads post-silicon enablement of design-for-test capabilities from silicon bring-up through production. Analyzes test data, quality, yield, efficiency, and failures; influences DFT architecture; develops validation, debug, deployment, and documentation methodologies; and supports test-time and power optimization. Collaborates with design, product, and test teams to connect pre-silicon decisions with production outcomes for advanced semiconductor devices.
Summary Generated by Built In

As a Senior DFT Engineer - Post-Silicon , you will take pioneering DFT capabilities beyond implementation—connecting silicon behavior, test data, and product learning to deliver robust, production-ready DFT solutions for NVIDIA’s most advanced chips.

NVIDIA has continuously reinvented itself over two decades. Our 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work , to amplify human imagination and intelligence. Make the choice to join us today.

What You’ll Be Doing:

  • Drive post-silicon enablement of DFT capabilities from initial silicon bring-up through production ramp and lifecycle support.

  • Develop data-driven approaches to analyze test results, quality indicators, yield behavior, and test efficiency; translate findings into practical technical recommendations.

  • Influence DFT architecture and implementation by communicating post-silicon requirements early with clear metrics/what-if analysis.

  • Define and improve methodologies for silicon bring-up, failure analysis, test-content validation, and production deployment.

  • Help productize new DFT capabilities by establishing scalable flows, validation criteria, debug procedures, and documentation.

  • Contribute to modeling and analysis that supports test-time optimization, quality improvement, yield learning, test power.

  • Partner across design, product development, and test teams to align pre-silicon trade-offs with post-silicon execution.

What We Need To See:

  • BSEE (or equivalent experience) with 8+ years or MS with 6 years of experience in related field.

  • Solid understanding of DFT concepts, silicon test, and the relationship between design implementation, test content, and post-silicon behavior.

  • Experience with silicon bring-up, debug, validation, production test, or engineering analysis of semiconductor devices.

  • Ability to analyze complex datasets and use statistical or analytical approaches to identify trends, isolate issues, and support engineering decisions.

  • Familiarity with automated test environments and test-program flows.

  • Understanding of semiconductor fundamentals, including device behavior, process variation, and the impact of operating conditions on silicon results.

  • Strong written and oral communication skills, with an ability to collaborate effectively across technical disciplines.

Ways To Stand Out From The Crowd:

  • Experience moving a silicon feature, test capability, or validation flow from development through production deployment.

  • Working knowledge of core DFT features—including scan, ATPG, and MBIST—together with silicon characterization and manufacturing test.

  • Experience developing scalable engineering workflows, automation, dashboards, or analysis tools.

Our technology has no boundaries! NVIDIA is building the world’s most groundbreaking and state of the art compute platforms for the world to use. It’s because of our work that scientists, researchers and engineers can advance their ideas. At its core, our visual computing technology not only enables an outstanding computing experience, but it is also energy efficient! We pioneered a supercharged form of computing loved by the most demanding computer users in the world - scientists, designers, artists, and gamers.

NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented 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 real passion for technology, we want to hear from you!

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 5, 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.

Skills Required

  • Bachelor of Science in Electrical Engineering or equivalent experience, with 8 or more years in a related field
  • Master of Science degree with 6 or more years of experience in a related field
  • Strong understanding of DFT concepts, silicon testing, design implementation, test content, and post-silicon behavior
  • Experience with silicon bring-up, debugging, validation, production testing, or semiconductor engineering analysis
  • Ability to analyze complex datasets using statistical or analytical methods
  • Familiarity with automated test environments and test-program flows
  • Understanding of semiconductor fundamentals, device behavior, process variation, and operating-condition effects on silicon results
  • Strong written and oral communication and cross-functional collaboration skills
  • Experience moving a silicon feature, test capability, or validation flow from development through production deployment
  • Working knowledge of scan, ATPG, MBIST, silicon characterization, and manufacturing test
  • Experience developing scalable engineering workflows, automation, dashboards, or analysis tools

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.

  • 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.
  • 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.
  • 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

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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