NVIDIA
Senior Performance Software Engineer, Deep Learning Libraries
NVIDIA, Hillsboro, Oregon, United States, 97104
Overview
We are looking for a Senior Performance Software Engineer for Deep Learning Libraries. You will develop optimized code to accelerate linear algebra and deep learning operations on NVIDIA GPUs. The team delivers high-performance code to NVIDIA’s cuDNN, cuBLAS, and TensorRT libraries to accelerate deep learning models. The work focuses on code lower in the deep learning software stack, close to the GPU hardware. We strive for peak GPU efficiency on current and future-generation GPUs. See our CUTLASS open-source project for an example of performant matrix multiply on Tensor Cores with CUDA. What You 27ll Be Doing
Writing highly tuned compute kernels, mostly in C++/CUDA, to perform core deep learning operations (e.g., matrix multiplies, convolutions, normalizations) Following general software engineering best practices including support for regression testing and CI/CD flows Collaborating with teams across NVIDIA: CUDA compiler team on generating optimal assembly code Deep learning training and inference performance teams on which layers require optimization Hardware and architecture teams on the programming model for new deep learning hardware features What We Need To See
Masters or PhD degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or related field 6+ years of relevant industry experience Strong C++ programming and software design skills, including debugging, performance analysis, and test design Experience with performance-oriented parallel programming Solid understanding of computer architecture and some experience with assembly programming Ways To Stand Out From The Crowd
Tuning BLAS or deep learning library kernel code CUDA/OpenCL GPU programming Numerical methods and linear algebra LLVM, TVM tensor expressions, or TensorFlow MLIR Salary and Benefits
Your base salary will be determined based on location, experience, and pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Application Information
Applications for this job will be accepted at least until October 24, 2025. NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate 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.
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We are looking for a Senior Performance Software Engineer for Deep Learning Libraries. You will develop optimized code to accelerate linear algebra and deep learning operations on NVIDIA GPUs. The team delivers high-performance code to NVIDIA’s cuDNN, cuBLAS, and TensorRT libraries to accelerate deep learning models. The work focuses on code lower in the deep learning software stack, close to the GPU hardware. We strive for peak GPU efficiency on current and future-generation GPUs. See our CUTLASS open-source project for an example of performant matrix multiply on Tensor Cores with CUDA. What You 27ll Be Doing
Writing highly tuned compute kernels, mostly in C++/CUDA, to perform core deep learning operations (e.g., matrix multiplies, convolutions, normalizations) Following general software engineering best practices including support for regression testing and CI/CD flows Collaborating with teams across NVIDIA: CUDA compiler team on generating optimal assembly code Deep learning training and inference performance teams on which layers require optimization Hardware and architecture teams on the programming model for new deep learning hardware features What We Need To See
Masters or PhD degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or related field 6+ years of relevant industry experience Strong C++ programming and software design skills, including debugging, performance analysis, and test design Experience with performance-oriented parallel programming Solid understanding of computer architecture and some experience with assembly programming Ways To Stand Out From The Crowd
Tuning BLAS or deep learning library kernel code CUDA/OpenCL GPU programming Numerical methods and linear algebra LLVM, TVM tensor expressions, or TensorFlow MLIR Salary and Benefits
Your base salary will be determined based on location, experience, and pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Application Information
Applications for this job will be accepted at least until October 24, 2025. NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate 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.
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