Senior Performance Software Engineer, Deep Learning Libraries

California Jobs; San Mateo (CA); On-site; USD 184,000 - 426,000; Full time

Job summary

A leading tech company is seeking a Senior Performance Software Engineer to optimize deep learning libraries and accelerate operations using NVIDIA GPUs. The role involves writing high-performance C++ CUDA code and collaborating on various software engineering tasks, ideal for those with strong background in computer science and engineering.

Benefits

Stock options

Health benefits

Work-life balance initiatives

Qualifications

• Masters or PhD degree in Computer Science, Computer Engineering, Applied Math.
• 6+ years of relevant industry experience.
• Strong C++ programming skills.

Responsibilities

• Writing compute kernels in C++ CUDA for deep learning operations.
• Supporting regression testing and CI/CD flows.
• Collaborating with multiple teams for optimizations.

Skills

C++ programming

software design

performance analysis

debugging

parallel programming

assembly programming

Education

Masters or PhD in Computer Science

Equivalent experience in Applied Math

Job description

Senior Performance Software Engineer, Deep Learning Libraries

We are now looking for a Senior Performance Software Engineer for Deep Learning Libraries! Do you enjoy tuning parallel algorithms and analyzing their performance? If so, we want to hear from you! As a deep learning library performance software engineer, you will be developing optimized code to accelerate linear algebra and deep learning operations on NVIDIA GPUs. The team delivers high-performance code to NVIDIA'scuDNN,cuBLAS, andTensorRTlibraries to accelerate deep learning models. The team is proud to play an integral part in enabling the breakthroughs in domains such as image classification, speech recognition, and natural language processing. Join the team that is building the underlying software used across the world to power the revolution in artificial intelligence! We're always striving for peak GPU efficiency on current and future-generation GPUs. To get a sense of the code we write, check out ourCUTLASS open-source project showcasing performant matrix multiply on NVIDIA'sTensor Cores with CUDA. This specific position primarily deals with code lower in the deep learning software stack, right down to the GPU HW.

What you'll 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

Demonstrated strong C++ programming and software design skills, including debugging, performance analysis, and test design

Experience with performance-oriented parallel programming, even if it's not on GPUs (e.g. with OpenMP or pthreads)

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

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.

The base salary range is 184,000 USD - 425,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

We are now looking for a Senior Performance Software Engineer for Deep Learning Libraries! Do you enjoy tuning parallel algorithms and analyzing their performance? If so, we want to hear from you! As a deep learning library performance software engineer, you will be developing optimized code to accelerate linear algebra and deep learning operations on NVIDIA GPUs. The team delivers high-performance code to NVIDIA'scuDNN,cuBLAS, andTensorRTlibraries to accelerate deep learning models. The team is proud to play an integral part in enabling the breakthroughs in domains such as image classification, speech recognition, and natural language processing. Join the team that is building the underlying software used across the world to power the revolution in artificial intelligence! We're always striving for peak GPU efficiency on current and future-generation GPUs. To get a sense of the code we write, check out ourCUTLASS open-source project showcasing performant matrix multiply on NVIDIA'sTensor Cores with CUDA. This specific position primarily deals with code lower in the deep learning software stack, right down to the GPU HW.

What you'll 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

• Demonstrated strong C++ programming and software design skills, including debugging, performance analysis, and test design

• Experience with performance-oriented parallel programming, even if it's not on GPUs (e.g. with OpenMP or pthreads)

• 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

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.

The base salary range is 184,000 USD - 425,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse 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.#deeplearning

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