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 designing abstractions for Tensor Core and related GPU hardware features in MLIR, Python, and C++ that enable writing high performance kernels, apply to join the CUTLASS team today!
What you'll be doing:
Develop core components of the CUTLASS platform including Tensor Core MMAs, copies, synchronization barriers, schedulers, and other GPU hardware features in CUDA C++ and CUTLASS Python DSL.
Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes.
Author example kernels utilizing CUTLASS abstractions to showcase the use of novel GPU hardware features that are crucial for achieving high performance.
Collaborate with GPU architecture, CUDA, and NVVM/PTX compiler teams to provide feedback on programming models and to assess the performance of future GPU hardware features.
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 working with high-performance code generation and knowledge of compiler transformations and optimizations.
A deep understanding of computer architecture and parallel computing programming models.
Ways to stand out from the crowd:
Experience writing high-performance kernels at low levels of abstractions like NVVM/ PTX for GPUs or other similar parallel processing architectures.
Hands-on compiler design experience, particularly in MLIR.
Understanding of deep learning models, algorithms, and 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 other objective job-related factors. The expected base salary ranges for this position are: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.Skills Required
- Master's or PhD degree in Computer Science, Computer Engineering, or a 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 high-performance code generation and knowledge of compiler transformations and optimizations
- Deep understanding of computer architecture and parallel computing programming models
- Experience writing high-performance GPU kernels using low-level abstractions such as NVVM or PTX
- Hands-on compiler design experience, particularly with MLIR
- Understanding of deep learning models, algorithms, and frameworks
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
