Senior Software Engineer, CUTLASS Platform

at Nvidia

📍 Santa Clara, United States

USD 152,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
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3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

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10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 4 CUDA Debugging @ 7 Deep Learning @ 4 GPU HPC Python

Details

NVIDIA's high-performance computing platforms power the AI revolution across many applications and industries. CUTLASS is an open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided C++ and Python abstractions for implementing custom matrix multiply (GEMM) and related mathematical and deep learning computations on NVIDIA GPUs.

The CUTLASS team is seeking an engineer passionate about designing abstractions for Tensor Core and related GPU hardware features in MLIR, Python, and C++ to enable the development of high-performance kernels.

Responsibilities

Develop core components of the CUTLASS platform, including Tensor Core MMAs, copies, synchronization barriers, schedulers, and other GPU hardware features using CUDA C++ and the CUTLASS Python DSL.
Contribute to the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes.
Author example kernels using CUTLASS abstractions to showcase 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 assess the performance of future GPU hardware features.

Requirements

Master's or PhD degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
At least 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.

Preferred Qualifications

Experience writing high-performance kernels at low abstraction levels, such as NVVM or PTX for GPUs, or for similar parallel processing architectures.
Hands-on compiler design experience, particularly with MLIR.
Understanding of deep learning models, algorithms, and frameworks.

Compensation and Benefits

The base salary is determined by location, experience, and the pay of employees in similar positions. The base salary ranges are:

Level 3: USD 152,000–241,500 per year
Level 4: USD 184,000–287,500 per year

The role also includes eligibility for equity and benefits. Applications will be accepted at least until June 5, 2026. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.