Job description

We are looking for a software engineering manager with strong leadership and mentoring skills to join the CUDA Driver team! We design the CUDA programming model, expose that programming model through the CUDA Driver & CUDA Runtime APIs, and implement the associated functionality in the CUDA Driver & CUDA Runtime. The CUDA Driver and its programming model serve as the foundation for NVIDIA’s CUDA-X software stack and compute platform. The team primarily works on aspects of the CUDA Driver related to its memory model – how to allocate , move, and access memory in a performant and efficient manner across NVIDIA’s range of hardware offerings, including both single-node and multi-node environments. What you will be doing: • Lead a team of system software engineers to design and build CUDA for current and future hardware architectures. • Engage multi-functionally with teams across NVIDIA to define and drive CUDA’s roadmap. • Contribute to CUDA feature design and drive adoption of new CUDA functionality. • Establish team objectives , prioritize incoming work , mentor team members, and manage team performance. • Monitor team execution, identify opportunities for process improvement, and take the lead on implementing any identified improvements. What we need to see: • 8+ overall years of experience in the software industry with 3+ years of management experience • Bachelors, Masters, or Ph.D. or equivalent experience in Computer Science, Computer Engineering, or a related field. • Strong system software fundamentals, hands-on C programming and debugging skills. • Ability to manage a team’s execution towards project deliverables, particularly in environments with competing priorities. Ways to stand out from the crowd: • In depth understanding of computer architecture and memory subsystems. • Experience implementing or directly using GPU programming APIs, such as CUDA, OpenCL, OpenGL, or Vulkan. • Background with distributed systems or high-performance clusters. • Experience with Deep Learning frameworks such as PyTorch , TensorFlow, or vLLM . Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 17, 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 a team of system software engineers to design and build CUDA for current and future hardware architectures.
Engage multi-functionally with teams across NVIDIA to define and drive CUDA’s roadmap.
Contribute to CUDA feature design and drive adoption of new CUDA functionality.
Establish team objectives , prioritize incoming work , mentor team members, and manage team performance.
Monitor team execution, identify opportunities for process improvement, and take the lead on implementing any identified improvements.
8+ overall years of experience in the software industry with 3+ years of management experience
Bachelors, Masters, or Ph.D. or equivalent experience in Computer Science, Computer Engineering, or a related field.
Strong system software fundamentals, hands-on C programming and debugging skills.
Ability to manage a team’s execution towards project deliverables, particularly in environments with competing priorities.
In depth understanding of computer architecture and memory subsystems.
Experience implementing or directly using GPU programming APIs, such as CUDA, OpenCL, OpenGL, or Vulkan.
Background with distributed systems or high-performance clusters.
Experience with Deep Learning frameworks such as PyTorch , TensorFlow, or vLLM .
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 17, 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

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