NVIDIA Logo

NVIDIA

Senior Failure Analysis Engineer

Reposted 9 Days Ago
Be an Early Applicant
In-Office
Santa Clara, CA, USA
144K-230K Annually
Senior level
In-Office
Santa Clara, CA, USA
144K-230K Annually
Senior level
Own reliability and continuous improvement of production-critical failure analysis systems; design scalable automation, data pipelines, analytics, and orchestration; apply AI/ML to accelerate root-cause analysis; partner with cross-functional semiconductor, CAD, and manufacturing teams; ensure operational excellence for large-scale production environments.
The summary above was generated by AI

NVIDIA is seeking a software-focused Senior Failure Analysis Engineer who can blend deep development with production support ownership. This hybrid role sits at the intersection of software engineering, data infrastructure, semiconductor development, and production tooling — building and sustaining the intelligent platforms and workflows that power failure analysis, debug, and engineering insight at scale.

You'll own the reliability and continuous improvement of production-critical FA systems (databases, CAD navigation tools, and analysis platforms) while partnering with failure analysis, design, verification, CAD, infrastructure, and manufacturing teams. This is a high-impact opportunity for someone who thrives on both building robust software and ensuring the tools that semiconductor teams depend on are always fast, reliable, and insightful.

What You'll Be Doing:

  • Own the reliability, performance, and continuous improvement of production-critical systems, including databases, CAD navigation tools, and failure analysis platforms, ensuring high availability and responsiveness for semiconductor engineering and manufacturing teams.

  • Design and deliver scalable automation frameworks, data pipelines, and intelligent workflows that streamline semiconductor engineering, failure analysis, and production support processes at scale.

  • Build advanced analytics platforms, dashboards, and orchestration systems that turn engineering and production data into clear, actionable insight for faster debug and better decision-making.

  • Apply AI, machine learning, and optimization techniques to reduce manual effort, accelerate root-cause analysis, and strengthen both engineering and production workflows.

  • Partner closely with failure analysis, design, verification, CAD, infrastructure, and production collaborators to deliver reliable, maintainable, and high-impact technical solutions.

  • Drive continuous improvement in software quality, usability, performance, and operational excellence across large-scale compute, data, and production environments.

What We Need to See:

  • BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field, or equivalent experience.

  • 8+ years of professional experience in software engineering, electrical engineering, or semiconductor development/production environments.

  • Strong proficiency in Python, Rust, Shell scripting, or similar languages for building robust automation, tooling, and production systems.

  • Proven track record designing automation frameworks, data-processing systems, or productivity tools with measurable engineering or production impact.

  • Solid experience in Linux environments and modern software engineering guidelines (version control, testing, CI/CD, observability).

  • Exceptional analytical and problem-solving skills with success navigating complex, multidisciplinary technical and production challenges.

  • Strong collaboration and communication skills with proven efficiency across multi-functional engineering and production teams.

Way to stand out from the crowd:

  • Direct experience in semiconductor design, silicon development, failure analysis, yield engineering, or engineering automation and production support workflows.

  • Hands-on application of AI/ML, data analytics, or optimization methods to technical, hardware, or production-related problems.

  • Familiarity with EDA workflows, design infrastructure, CAD navigation systems, or semiconductor tooling and lab/production environments.

  • Track record architecting and operating scalable data pipelines, analytics platforms, or workflow orchestration systems in production settings.

  • Proven ability to independently scope, drive, and deliver technical projects end-to-end while balancing development and production support responsibilities in fast-paced environments.

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 thoughtful and dedicated people in the world working for us. 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 the pay of employees in similar positions. The base salary range is 144,000 USD - 230,000 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 16, 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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

Similar Jobs

5 Days Ago
In-Office
135K-195K Annually
Senior level
135K-195K Annually
Senior level
Aerospace • Other
The Sr. Failure Analysis Engineer will analyze production failures, support investigations, and ensure product quality through various analysis techniques throughout product life cycles.
Top Skills: Chemical DecapsulationCsamCt ScanEee Piece PartsFailure Analysis EquipmentExcelObirchPowerPointSemSmt ManufacturingVisual InspectionWordX-Ray
An Hour Ago
In-Office
San Jose, CA, USA
119K-202K Annually
Mid level
119K-202K Annually
Mid level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
The Armed Executive Protection Agent is responsible for providing protective services to high-profile clients, conducting threat assessments, and ensuring client safety in various environments.
Top Skills: AedCprFirst AidTactical Communications
An Hour Ago
In-Office
San Jose, CA, USA
168K-336K Annually
Senior level
168K-336K Annually
Senior level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Design and build advanced verification environments using UVM/SystemVerilog and GenAI/agentic tools to improve verification efficiency and quality. Develop test plans, drive coverage closure, and verify SoC and CPU emulation platforms using ASIC simulation tools and scripting to achieve signoff and schedule left-shift.
Top Skills: Agentic McpAsic Simulation ToolsC++Cpu EmulationGenaiScriptingSocSystemcSystemverilogUvm

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account