Manager CUDA Systems Software
NVIDIA
Manager CUDA Systems Software
NVIDIA
Designs the chips and software that power AI
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 stackand compute platform. The team primarily works on aspects of the CUDA Driver related to its memory model – how toallocate, move, and access memory in a performant and efficient manner across NVIDIA’s range of hardware offerings, includingboth 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 teamobjectives, prioritize incoming work,mentor team members, andmanage team performance.
Monitor team execution,identifyopportunities 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, ora relatedfield.
Strong systemsoftware fundamentals, hands-on Cprogrammingand 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 depthunderstanding 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 asPyTorch, TensorFlow, orvLLM.
You will also be eligible for equity and benefits.
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.NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
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