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Research Scientist, Efficient Deep Learning - New College Grad 2024

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NVIDIA

Apr 23

  • Job
    Full-time
    Entry Level
  • Research & Development
    Software Engineering
  • $160K - $253K
  • Santa Clara
  • Quick Apply

AI generated summary

  • You need a Ph.D. in CS/EE or research exp., strong computer vision & deep learning knowledge, experience in pruning/quantization/NAS, and Python/PyTorch skills. CUDA, large-scale model training, and a solid research track record are essential.
  • You will research, design, and implement efficient deep learning methods, publish research, collaborate with teams, mentor interns, speak at events, and transfer technology to product groups.

Requirements

  • Completing or recently completed a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or have equivalent research experience.
  • Excellent knowledge of theory and practice of computer vision methods, as well as deep learning.
  • Background in pruning, quantization, NAS, efficient backbones, and so on, is expected.
  • Experience with large language models and large vision-language models is a plus.
  • Excellent programming skills in Python and PyTorch; C++ and parallel programming (e.g., CUDA) is a plus.
  • Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.
  • Outstanding research track record.
  • Excellent communications skills.

Responsibilities

  • Research, design and implement novel methods for efficient deep learning.
  • Publish original research.
  • Collaborate with other team members and teams.
  • Mentor interns.
  • Speak at conferences and events.
  • Work with product groups to transfer technology.
  • Collaborate with external researchers.

FAQs

What type of research will I be working on as a Research Scientist in Efficient Deep Learning at NVIDIA?

You will be focusing on efficient deep learning research, specifically methods for post-training model optimization, efficient architecture design, adaptive/dynamic inference, resource-efficient training and finetuning, and more.

What kind of impact can my research have on NVIDIA's products in this role?

Your research has the potential to create real impact on NVIDIA's products by improving efficiency and performance in deep learning models.

What kind of expertise does the learning and perception research team at NVIDIA have?

The team has expertise in computer vision, deep learning, generative models, and other related areas, and consistently publishes in top venues in computer vision and machine learning.

How collaborative is the research team at NVIDIA?

The research team is described as amazing and collaborative, providing a supportive environment for researchers to work together towards impactful goals.

NVIDIA

Manufacturing & Electronics
Industry
10,001+
Employees
1993
Founded Year

Mission & Purpose

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.