[Remote] Security Engineer, GPU Kernel Driver
Note: The job is a remote job and is open to candidates in USA. NVIDIA is a technology company advancing graphics, gaming, AI, and accelerated computing through GPU-powered systems. The Security Engineer will secure GPU kernel and firmware components by managing vulnerability remediation, leading security analysis pipelines, communicating risk, and driving software and hardware hardening initiatives.
Responsibilities
- Own the security vulnerability backlog for kernel and firmware components, driving timely triage, remediation and SLA compliance; identify creative, scalable approaches to reduce backlog growth
- Lead a continuous security pipeline scanning, triage, root-cause analysis, remediation and validation across SW and FW components, communicate security risks to stakeholders effectively
- Communicate security risks, security posture and remediation progress through metrics, reports and stakeholder engagement
- Partner with engineering and security teams to define and execute long-term security strategy and product hardening efforts
- Drive and implement security reviews of software and hardware designs, assisting others to ensure the quality and robustness of our products
- Evaluate, recommend, and develop cutting edge security technologies, tools, and practices: static analysis for security enforcements, dynamic analysis solutions for fuzzing
Skills
- Bachelor's or Master's degree in Computer Science, Engineering or equivalent experience
- 5+ years of relevant industry software engineering experience
- Experience with security analysis of complex systems
- Demonstrated strong technical background; excellent C programming and low-level driver experience
- Knowledge of operating systems and computer architecture fundamentals
- Strong communication, troubleshooting, and debugging skills
- Experience with secure code quality practices and tooling to support quick engagements and rapid analysis: static analysis tools (Coverity, Checkmarx, or similar), dynamic scanning (Rapid 7, AppSider, or similar), Fuzzing (AFL, Peach, or similar), code coverage (Bullseye, LDRA, etc.)
- Experience applying AI/LLM-based tools and agentic workflows
- Experience with vulnerability research
- Understanding of secure software development lifecycle standard methodologies, e.g. threat modeling, unit testing, incident response, etc
- Shown skills in working in large geographically distributed teams
Benefits
- You will also be eligible for equity and benefits.
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