Applied Deep Learning Research Scientist, Sparsity

3 Months ago • 3 Years + • Artificial Intelligence • Research & Development • $160,000 PA - $299,000 PA

Job Summary

Job Description

This applied research role focuses on developing sparsity-related techniques for neural networks, aiming to improve the efficiency of deep learning accelerators and software. Responsibilities include researching methods to enable sparsity while maintaining result quality, proposing hardware features to support sparsity, analyzing their impact on acceleration and efficiency, publishing research findings, and collaborating with internal and external researchers and practitioners. The successful candidate will contribute to the advancement of AI technologies at NVIDIA.
Must have:
  • MS/PhD in CS/EE or related field
  • 3+ years relevant experience
  • Neural network pruning and sparsity expertise
  • DL framework/inference engine experience
  • Computer architecture background
  • Proficiency in Python/C++
Good to have:
  • GPU computing experience
  • CUDA experience
Perks:
  • Equity
  • Benefits

Job Details

We are now looking for an Applied Deep Learning Research Scientist with a focus on Sparsity:

We are seeking DL researchers and/or computer architects to help future accelerators and neural networks take advantage of sparsity. This is an applied research position, with the goal of developing sparsity-related techniques (in isolation and combined with reduced precision) and transferring the most promising to SW and HW products. Work entails investigations, publication, and collaboration with researchers and practitioners (internal and external to NVIDIA).

What you'll be doing:

  • Researching methods (adjusting model architectures, training procedures, etc.) to enable sparsity in neural networks while maintaining the quality of the results.

  • Proposing hardware features to enable sparsity, studying their impact on DL acceleration and efficiency.

What we need to see:

  • MS or PhD degree in computer science, computer engineering, electrical engineering or related field or equivalent experience.

  • At least 3+ years of relevant work experience

  • Experience with neural network pruning and sparsity, training networks for various tasks, exploring model architectures.

  • Experience with modern DL training frameworks and/or inference engines.

  • Background in computer architecture, performance analysis and optimization.

  • Fluency in Python, C++, or ideally both.

  • Experience with GPU computing, CUDA is not required but a big plus.

Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. The era of AI has begun.

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!

The base salary range is 160,000 USD - 299,000 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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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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