GPU SW Security Engineer

at Nvidia

📍 Santa Clara, United States

USD 152,000-241,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI CI/CD @ 4 GPU LLM @ 4 Python @ 7 Security @ 6

Details

NVIDIA is seeking a highly motivated security engineer to join the GPU Software team. The role focuses on automating security enforcement across every software release using traditional tooling and AI agents, while helping engineering teams adopt these solutions.

Responsibilities

Lead the adoption of AI agents for security by identifying manual workflows and redesigning them.
Develop proven agentic workflows and take them into production, driving adoption across engineering teams.
Translate security requirements, including hardening flags, isolation mechanisms, and security invariants, into automated per-release checks for software ranging from firmware to user-mode applications.
Own and maintain the release security scanning pipeline and prioritize findings with product teams.
Contribute to broader security engineering activities, including threat modeling, architecture reviews, vulnerability mitigation, and remediation.

Requirements

5+ years of experience in security engineering, with experience in drivers, kernels, or firmware.
Strong programming skills in Python and C.
Hands-on experience building LLM agents or agentic workflows.
Experience integrating tooling into CI/CD and release pipelines.
A track record of taking an internal tool from prototype to broad adoption without direct authority.
BS or MS degree in Computer Engineering, Computer Science, or a related field.

Preferred Qualifications

Experience applying isolation mechanisms such as sandboxing, containers, virtualization, and privilege separation.
Experience building or maintaining static or binary analysis tooling.
Experience defining security baselines or policy-as-code.
Solid understanding of toolchains such as GCC and GDB.