Senior Embedded System Software Engineer - Hypervisor and RTOS

Reposted Yesterday
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4 Locations
In-Office or Remote
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and implement RTOS and hypervisor architectures for automotive systems. Ensure safety and security compliance while enhancing software quality using formal methods.
Summary Generated by Built In

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.
 

The Hypervisor and RTOS Team within NVIDIA DRIVE Software plays a critical role in NVIDIA's expansion into the world of artificial intelligence and autonomous vehicles. Our job is to facilitate the sharing and separation of system resources while achieving real-time, safety, and security requirements. We develop Hypervisor and RTOS with a strong focus on automotive quality, safety and security needed for the real-time, highly available system level components of world-class Autonomous Vehicles. We are making extensive use of formal methods to automate our workflow and increase the quality of our SW. We are hiring now for the position of Senior System Software Engineer for Hypervisor and RTOS
 

What you’ll be doing:

  • Design and implement extensible RTOS and hypervisor architectures that support multiple SoCs and CPU architectures through modular, portable system components.

  • Implement and maintain backward compatibility mechanisms across RTOS and hypervisor releases, including stable APIs/ABIs, configuration compatibility, and legacy platform support.

  • Design and implement core virtualization features that leverage hardware-assisted virtualization on NVIDIA Tegra SoCs based on ARM architecture, optimizing performance and efficiency.

  • Develop software that meets automotive safety and security standards, and apply formal methods to improve software integrity.

What we need to see:

  • BS, MS in CS/CE/EE or a related engineering field or equivalent experience

  • 8+ years of experience

  • Proficiency in C, C++

  • Experience in development of core rtos and virtualization software features

  • Strong understanding of operating systems and computer architecture

  • Experience on ARM 64-bit architecture

  • Clear, concise communication skills

Ways to stand out from the crowd:

  • Knowledge of Automotive quality standards, ASPICE, ISO 26262, ISO 21434

  • Hands-on experience with formal verification methods and tools, such as TLA+
     

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 January 26, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

Top Skills

Arm Architecture
C
C++
Hypervisor
Rtos
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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