Role at a glance
- Salary
- $152K – $287.5K/yr
- Location
- 5 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 3+ years of relevant industry experience.
- Education
- Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).
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Role Summary
The CUTLASS team develops high-performance linear algebra and Tensor Core primitives for NVIDIA GPUs through CUDA C++ and Python abstractions. This role focuses on delivering optimized deep learning and mathematical kernels for current and future NVIDIA architectures, supporting performance on hardware and software simulators.
What You'll Do
- Write Tensor Core-based deep learning kernels such as grouped-GEMM, attention, and convolution using CUTLASS CUDA C++ and Python DSL.
- Optimize kernels for peak throughput on silicon and software performance simulators.
- Collaborate with GPU architecture, NVVM/PTX compiler, CUDA library, and deep learning framework teams to support fast, functional, and...
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View full postingQualifications
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 another language targeting highly parallel accelerators; deep understanding of computer architecture and some experience working at the assembly level.
Required
- 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
- Debugging, performance evaluation, and testing
- Experience with a programming language targeting highly parallel accelerators
- Deep understanding of computer architecture
- Some experience working at the assembly level
Preferred
- Experience writing code specifically targeting NVIDIA Tensor Cores, particularly through PTX or CUDA/cuTile
- Open-source contributions to math kernel libraries or frameworks
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.