NVIDIA, widely recognized as one of the world’s most desirable employers, believes open-weight models are foundational to American AI leadership, cybersecurity, and defense through broad scientific scrutiny. As part of this mission, our AI Safety & Security Engineering team builds and evaluates AI-powered tooling that finds, validates, and patches software vulnerabilities, recognizing that finding a bug is only the beginning. We are seeking a Security Research Engineer to advance our Validate and Patch capabilities by establishing what counts as a confirmed vulnerability and defining what constitutes a truly correct, safe fix. In this critical role, you will apply rigorous security judgment to well-defined categories of vulnerabilities. These affect NVIDIA-internal targets. You will turn complex analysis into repeatable methods that improve software people rely on daily.
Validation here requires meticulous care to confirm reports are real and reachable rather than noise, while patching requires ensuring fixes repair flaws, protect existing behavior, and hold up under strict revalidation. Working alongside harness and evaluation engineers, you will establish high engineering standards, document your reasoning for independent security reviews, and ensure your methods run reliably with fully traceable evidence. AI-assisted workflows are an integral part of this job, but so is maintaining a healthy, disciplined skepticism about their outputs. Beyond immediate fixes, your work will teach the entire program what trustworthy patching looks like while actively helping decide which vulnerability classes the team tackles next. Ultimately, we hold our results to an exceptionally high bar and value specific, verifiable proof of your technical expertise—such as CVEs, advisories, or original security tools—over polished phrasing.
What You'll Be Doing:
Validation methods: Develop techniques that confirm vulnerabilities are real and reachable.
Patch methods: Advance approaches for generating and verifying safe fixes.
Quality standards: Define correctness, regression, and revalidation standards with reviewers.
Applied research: Work bounded vulnerability classes against internal targets.
What We Need To See:
Bachelor's degree (or equivalent experience) with 12+ years in security research or software engineering.
Security foundations: Hands-on vulnerability research, fuzzing, program analysis, or secure development in C, C++, or Python.
Fix quality: Rigor about what makes a fix correct and safe, including regression and behavior preservation.
AI-assisted workflows: Comfort using AI-assisted tools for analysis and development.
Ways to Stand Out from the Crowd:
Public research: CVEs, advisories, or publications in vulnerability research.
Analysis tooling: Experience building or extending fuzzers, static analyzers, or symbolic-execution tools.
Agentic ML: Familiarity with LLM-based coding or analysis agents.
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: Confidential Computing and Data. If you're a creative engineer who enjoys autonomy and shares our 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 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.You will also be eligible for equity and benefits.
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's degree (or equivalent experience) with 12+ years in security research or software engineering.
- Hands-on vulnerability research, fuzzing, program analysis, or secure development in C, C++, or Python.
- Rigor about what makes a fix correct and safe, including regression and behavior preservation.
- Comfort using AI-assisted tools for analysis and development.
- Public research such as CVEs, advisories, or vulnerability research publications.
- Experience building or extending fuzzers, static analyzers, or symbolic-execution tools.
- Familiarity with LLM-based coding or analysis agents (agentic ML).
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.”
