We are now looking for an Offensive Hardware Security Researcher!
NVIDIA is seeking an outstanding Offensive Hardware Security Researcher to work on a wide variety of security research challenges. Do you excel at thinking like an attacker, identifying hardware weaknesses, creating tools and automation for hardware vulnerability research? Join our team to hack the future, fortify the silicon frontier, and shape the destiny of groundbreaking chip technology!
What you will be doing:
Research vulnerabilities on cutting-edge SoC and GPU designs
Develop and use cutting-edge security tools and techniques
Guide the continuous integration of latest mitigations into our security architecture
Research and exploit side-channel, fault, and advanced physical attacks
What we need to see:
BS/BA degree in Computer Science or Computer Engineering or Electrical Engineering or equivalent experience
6+ years of work experience in a Security related field
Experience with ARM/RISCV assembly, Verilog and low-level C programming
Understanding of large SoC and ASIC architecture and design
Experience with security code reviews of complex firmware projects and defensive coding best practices (SDL, threat modeling)
Ability to work collaboratively and remotely with multiple experts to accomplish complex goals
Expertise in two of more of the following fields:
Expertise in side-channel analysis and mitigation for cryptographic primitives
TEE (TrustZone, SE), Confidential Computing, and/or microarchitectural attacks
Proficiency with Symbolic Execution and/or fuzzing tools
JTAG, debugging, binary instrumentation frameworks, ChipWhisperer
Reverse-engineering (IDA Pro, Ghidra)
Practical experience in utilizing machine learning techniques for performing side-channel attacks
Track record of advancing offensive security research field through vulnerability discoveries, research publications, and/or developing security tools
Ways to stand out from the crowd:
Understanding of pre-silicon hardware design and testing
Knowledge of key hardware security architecture components, and their implementation in complex SoC designs
Strong background in computer architecture, especially GPU or AI accelerator design
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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. 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 forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, 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 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.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
- BS/BA in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience
- 6+ years of work experience in a security-related field
- Experience with ARM and RISC-V assembly, Verilog, and low-level C programming
- Understanding of large SoC and ASIC architecture and design
- Experience performing security code reviews of complex firmware and applying defensive coding best practices (SDL, threat modeling)
- Ability to work collaboratively and remotely with multiple experts to accomplish complex goals
- Expertise in at least two of: side-channel analysis/mitigation, TEE (TrustZone/SE)/Confidential Computing, microarchitectural attacks, symbolic execution, fuzzing tools, JTAG/debugging/binary instrumentation/ChipWhisperer, reverse-engineering (IDA Pro, Ghidra), or ML techniques for side-channel attacks
- Track record of advancing offensive security research via vulnerability discoveries, publications, or security tools
- Understanding of pre-silicon hardware design and testing
- Knowledge of hardware security architecture components and their implementation in complex SoC designs
- Strong background in computer architecture, especially GPU or AI accelerator design
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.”
