NVIDIA's invention of the GPU 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, we are increasingly known as “the AI computing company”
NVIDIA is hiring Software Engineers with AI Compiler experience for its Deep Learning Compiler Technology team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in problems from image classification to speech recognition to natural language processing and artificial intelligence. Join the team which is developing advanced technology for the software which will be used by the entire deep learning community.
What you'll be doing:
In this role, you will be doing technology development on problems of kernel generation and optimizations for computational graphs for NVIDIA GPUs. The goal of this work will be to advance the state of the art in compilation problem of DL graphs for current and future NVIDIA GPUs and transfer this tech to product. In particular the problems of interest will be drawn from computational graphs as encountered in inference and training workloads. Develop, both, online and offline techniques for use in the production compiler NVIDIA is developing. You will deploy your research to automatically produce high performance code, often, matching and exceeding the abilities of GPU architects in new ways to generate high performance libraries You will also have the opportunity to publish your research in peer reviewed conferences and journals. As part of you role you will also be responsible for technology transfer to production groups.
What we need to see:
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Masters or PhD or equivalent experience in Computer Science, Computer Engineering, or related field.
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3+ years of relevant work or research experience in compiler optimizations, synthesis, super optimization and computer architecture.
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Be able to work independently, define project goals and scope, and lead your own research and development efforts
- C++ and/or Python experience
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Excellent programming and software design skills, including debugging, performance analysis, and test design.
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Experience with the following technologies is a huge plus:
Deep learning models and algorithms
Polyhedral methods
Program synthesis
Tile based IR and domain specific languages
MLIR experience
Autotuning
Deep learning framework design
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Strong communication skills are required along with the ability to work in a dynamic product oriented team. A history of mentoring early career engineers and interns is a bonus.
Ways to stand out from the crowd:
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Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience desired but not required
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you!
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!
The base salary range is 148,000 USD - 419,750 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.
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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.”
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