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Senior Systems Software Engineer – GPU Software

NVIDIA Corporation

US, CA, Santa ClaraKernel / LinuxFirmwarePosted Sep 15, 2026
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Skills named in this posting

  • C
  • C++
  • Linux kernel
  • Virtualization
NVIDIA is seeking an innovative and highly motivated engineer with deep expertise in systems software to join our GPU Software team. In this role, you will help design and develop key components of our production GPU kernel drivers and embedded software, shaping products used across both datacenter and gaming markets. What you'll be doing: • Design, develop, and verify features for next-generation GPU driver architecture in close collaboration with hardware and software engineering teams • Help identify and solve performance bottlenecks in our driver, both in markets of scale like datacenter as well in gaming markets where applications need to run as fast as possible; help shape robust, scalable driver solutions for both compute and graphics environments • Collaborate with globally distributed teams to deliver scalable, reliable, and high-impact GPU software solutions What we need to see: • BS or MS degree in Computer Engineering, Computer Science, or related fields (or equivalent experience) • 5+ years of relevant software development experience • Proven leadership skills and strong ownership of past projects • Hands on technical experience and demonstrated excellence in an environment with sophisticated software and hardware designs • Exceptional C/C++ programming and low-level driver experience; background and strength with complex system-level debugging • Kernel experience with Linux, Android, Chrome, or Windows systems • Familiarity and comfort with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.) Ways to stand out from the crowd: • Experience as a maintainer or contributor to large open source software projects • Experience with CI/CD pipelines, Containerization, Docker, Kubernetes, Environment provisioning, YAML-based pipeline configuration • Knowledge of virtualization platforms (XenServer, KVM, Hyper-V) • Familiarity with kernel level security concepts; this includes testing techniques and a familiarity with static code analysis, dynamic analysis, fuzzing, negative testing and other techniques NVIDIA is broadly recognized as one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, passionate and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until September 19, 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.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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