Job description

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle. Within NVIDIA DRIVE Software, the Hypervisor and RTOS Team contributes significantly to NVIDIA's advancement in artificial intelligence and autonomous vehicles. Our mission is to manage system resource sharing and separation while fulfilling real-time, safety, and security needs. We design Hypervisor and RTOS focusing on automotive quality, safety, and security required by the real-time, highly reliable system parts of leading Autonomous Vehicles. We are hiring now for the position of Senior Security Engineer, RTOS and Virtualization What you’ll be doing: • Lead security engineering for RTOS, hypervisor, and embedded virtualization technologies across design, implementation, review, and verification. • Collaborate on CPU and SoC architecture, including privilege levels, memory protection, DMA, interrupts, boot flows, debug controls, and hardware isolation. • Build and implement defensive features such as strong partitioning, least-privilege access, secure communication, fault containment, secure updates, and recovery from malicious inputs. • Perform threat modeling and automotive TARA, and connect risks, mitigations, requirements, tests, and evidence to security and safety standards. • Review low-level C/C++ code, investigate vulnerabilities, build fuzzing and security test infrastructure, and drive fixes into production. What we need to see: • 8+ years of hands-on experience in systems, embedded, platform, product, or automotive security. • BSEE/ BSCS degree or equivalent experience • Experience securing RTOS, hypervisor, kernel, firmware, boot, driver, or other privileged software. • Strong C/C++ skills, with focus on memory safety, concurrency, resource ownership, privilege boundaries, and isolation. • Familiarity with CPU and SoC security concepts including MMU/SMMU or IOMMU, DMA, interrupts, boot, debug, and hardware-backed isolation. • Experience with threat modeling, vulnerability analysis, exploitability assessment, fuzzing, static or dynamic analysis, and security remediation. • Familiarity with automotive cybersecurity, safety, or process standards such as ISO/SAE 21434, UN R155, ISO 26262 interfaces, or Automotive SPICE. Ways to stand out from the crowd: • Drove adoption of Rust, Ada/SPARK, formal methods, or other memory-safe and analyzable systems approaches. • Built capability-based or ownership-based security models for low-level systems. • Built security automation, fuzzing infrastructure, review agents, or AI-assisted tools used by engineering teams. 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 . Applications for this job will be accepted at least until October 3, 2026. 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.

Requirements

Must-haves

Lead security engineering for RTOS, hypervisor, and embedded virtualization technologies across design, implementation, review, and verification.
Collaborate on CPU and SoC architecture, including privilege levels, memory protection, DMA, interrupts, boot flows, debug controls, and hardware isolation.
Build and implement defensive features such as strong partitioning, least-privilege access, secure communication, fault containment, secure updates, and recovery from malicious inputs.
Perform threat modeling and automotive TARA, and connect risks, mitigations, requirements, tests, and evidence to security and safety standards.
Review low-level C/C++ code, investigate vulnerabilities, build fuzzing and security test infrastructure, and drive fixes into production.
8+ years of hands-on experience in systems, embedded, platform, product, or automotive security.
BSEE/ BSCS degree or equivalent experience
Experience securing RTOS, hypervisor, kernel, firmware, boot, driver, or other privileged software.
Strong C/C++ skills, with focus on memory safety, concurrency, resource ownership, privilege boundaries, and isolation.
Familiarity with CPU and SoC security concepts including MMU/SMMU or IOMMU, DMA, interrupts, boot, debug, and hardware-backed isolation.
Experience with threat modeling, vulnerability analysis, exploitability assessment, fuzzing, static or dynamic analysis, and security remediation.
Familiarity with automotive cybersecurity, safety, or process standards such as ISO/SAE 21434, UN R155, ISO 26262 interfaces, or Automotive SPICE.
Drove adoption of Rust, Ada/SPARK, formal methods, or other memory-safe and analyzable systems approaches.
Built capability-based or ownership-based security models for low-level systems.
Built security automation, fuzzing infrastructure, review agents, or AI-assisted tools used by engineering teams.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningrustai

Platform: eightfold
Effort: medium