GPU SW Security Engineer

Nvidia

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Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 6 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $198k

This role $197k

$140k most similar roles pay here $252k

This role pays more than 50% of similar roles. Most pay $164,250–$231,812 — the shaded band above. At the midpoint, this role pays about $197k versus about $198k for comparable roles.

Based on 240 similar postings.

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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1391 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1116 roles with salary data.

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At a glance

TL;DR · GPU SW Security Engineer

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As a GPU SW Security Engineer on the GPU Software team, you will focus on automating security enforcement across every software release using traditional tooling and AI agents. You will lead the adoption of agentic workflows by identifying manual processes and reinventing them for production use while driving adoption across engineering teams. Your daily responsibilities include translating security requirements like hardening flags and isolation mechanisms into automated checks for firmware and user-mode applications, maintaining the release scanning pipeline, and performing threat modeling and vulnerability remediation. The role requires proficiency in Python and C, experience with LLM agents, and integration of tools into CI/CD pipelines. You will address technical challenges involving drivers, kernel, or firmware security while utilizing skills in sandboxing, virtualization, static analysis, and toolchains like GCC and GDB to ensure robust software integrity.

Skills

Python C LLM Agents CI/CD Firmware Kernel Sandboxing Containers Virtualization Binary Analysis Policy-as-Code GCC GDB Threat Modeling

What you'll do

Lead the adoption of AI agents to automate and reinvent manual security workflows.
Develop and deploy agentic workflows from initial development into production environments.
Translate security requirements into automated checks for software ranging from firmware to user-mode applications.
Own and maintain the release security scanning pipeline while prioritizing findings with product teams.
Perform threat modeling, architecture reviews, and vulnerability mitigation across the organization.
Integrate security tooling into CI/CD and release pipelines.
Drive the adoption of automated security tools across various engineering teams.

What we're looking for

5+ years of experience in security engineering with experience in drivers, kernel, 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.
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.
Application of isolation mechanisms such as sandboxing, containers, virtualization, and privilege separation (preferred).
Experience with static/binary analysis tools, policy-as-code, or toolchains like GCC and GDB (preferred).

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