Job description

NVIDIA's high-performance computing platforms are powering the AI revolution across many applications and industries. Within our software stack, CUTLASS stands out as a popular open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs. If you are passionate about developing and optimizing math kernels to extract the highest performance out of the hardware architecture, apply to join the CUTLASS team today! What you'll get to do: • Write Tensor Core-based deep learning kernels such as grouped-GEMM, attention, and convolution using CUTLASS CUDA C++ and Python DSL for Blackwell, Rubin, and future architectures. • Optimize kernels for peak throughput on both silicon and software performance simulators. • Collaborate with teams across NVIDIA including the GPU architecture, NVVM/PTX compiler, CUDA library, and DL frameworks teams to ensure fast, functional, and timely kernel delivery to customers. What we need to see: • Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience). • 3+ years of relevant industry experience. • Strong proficiency in C++ programming and software design, including debugging, performance evaluation, and testing. • Experience with CUDA, OpenCL, HIP, SYCL, Mojo, Pallas, Triton, Mosaic, Halide, or any general-purpose or domain-specific programming language targeting highly parallel accelerators. • Deep understanding of computer architecture and some experience working at the assembly level. Ways to stand out from the crowd: • Experience writing code specifically targeting NVIDIA Tensor Cores, particularly through PTX or CUDA/cuTile. • Open-source contributions to math kernel libraries or frameworks. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us. If you're creative, autonomous, and love a challenge, consider joining our Deep Learning Library team and help us build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. 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 for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until June 5, 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

If you are passionate about developing and optimizing math kernels to extract the highest performance out of the hardware architecture, apply to join the CUTLASS team today!
Write Tensor Core-based deep learning kernels such as grouped-GEMM, attention, and convolution using CUTLASS CUDA C++ and Python DSL for Blackwell, Rubin, and future architectures.
Optimize kernels for peak throughput on both silicon and software performance simulators.
Collaborate with teams across NVIDIA including the GPU architecture, NVVM/PTX compiler, CUDA library, and DL frameworks teams to ensure fast, functional, and timely kernel delivery to customers.
Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).
3+ years of relevant industry experience.
Strong proficiency in C++ programming and software design, including debugging, performance evaluation, and testing.
Experience with CUDA, OpenCL, HIP, SYCL, Mojo, Pallas, Triton, Mosaic, Halide, or any general-purpose or domain-specific programming language targeting highly parallel accelerators.
Deep understanding of computer architecture and some experience working at the assembly level.
Experience writing code specifically targeting NVIDIA Tensor Cores, particularly through PTX or CUDA/cuTile.
Open-source contributions to math kernel libraries or frameworks.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until June 5, 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

aipython

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