Posted Aug 16

Nvidia is hiring a
Research Scientist – AI Compilers

US, WA, Redmond • US, CA, Santa Clara • US, CA, Santa Clara • 2 Locations
Full time

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 Research Scientists with AI 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 research 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. 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:

  • Masters or PhD or equivalent experience in Computer Science, Computer Engineering, or related field.

  • 3+ years of relevant work or research experience in compiler optimizations, synthesis, super optimization and computer architecture.

  • Be able to work independently, define project goals and scope, and lead your own research and development efforts

  • Excellent programming and software design skills, including debugging, performance analysis, and test design.

  • 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

Autotuning

Deep learning framework design

  • Strong communication skills are required along with the ability to work in a dynamic product oriented team. A history of mentoring junior engineers and interns is a bonus.

Ways to stand out from the crowd:

  • Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience desired but not required

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

The base salary range is $144,000 - $270,250. 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 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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