Offensive Hardware Security Researcher

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking an Offensive Hardware Security Researcher to identify and exploit hardware vulnerabilities in SoC and GPU designs. The role involves developing security tools, researching attacks (side-channel, fault, physical), and guiding mitigation integration. Requires expertise in low-level programming, SoC architecture, and specific security fields like side-channel analysis, TEE, symbolic execution, or reverse-engineering. A track record of advancing offensive security research is valued.

What you'd actually do

  1. Research vulnerabilities on cutting-edge SoC and GPU designs
  2. Develop and use cutting-edge security tools and techniques
  3. Guide the continuous integration of latest mitigations into our security architecture
  4. Research and exploit side-channel, fault, and advanced physical attacks

Skills

Required

  • 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 side-channel analysis and mitigation for cryptographic primitives
  • Expertise in 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

Nice to have

  • 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

What the JD emphasized

  • Expertise in two of more of the following fields
  • Practical experience in utilizing machine learning techniques for performing side-channel attacks