Research Scientist, Efficient Deep Learning

Nvidia

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Work type
On-site
Location
Santa Clara, CA
Employment
Full-time
Posted
138 days ago
Freshness
Confirmed live today

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Similar $201k
$148k $261k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $160,450–$241,750.

Based on 240 similar postings.

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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Research Scientist, Efficient Deep Learning

Research Scientist, Efficient Deep Learning - New College Grad 2026 will join the deep learning efficiency research team to develop methods that push boundaries while maintaining real-world impact. The role involves researching, designing, and implementing novel methods for efficient deep learning, publishing original research, mentoring interns, and collaborating with product groups to transfer technology. Key responsibilities include working on post-training model optimization such as pruning, quantization, and NAS, as well as efficient architecture design and resource-efficient training. Candidates must possess expertise in computer vision, deep learning, and large language models. Required skills include Python, PyTorch, and hands-on experience with large-scale model training, data preparation, and model parallelization. Knowledge of C++ and CUDA is a plus for solving complex technical problems in generative models.

What does a Research Scientist earn?

Median $216250 from 45 postings across 16 companies.

See salary data

What you'll do

  • Research, design, and implement novel methods for efficient deep learning.
  • Publish original research in top-tier computer vision and machine learning venues.
  • Mentor interns and provide guidance on research projects.
  • Speak at industry conferences and research events.
  • Work with product groups to transfer research technology into products.
  • Perform large-scale model training including data preparation and model parallelization.

What we're looking for

  • Complete or recently completed a Ph.D. in Computer Science, Engineering, Electrical Engineering, or equivalent research experience.
  • Excellent knowledge of the theory and practice of computer vision methods and deep learning.
  • Experience with large language models and large vision-language models.
  • Hands-on experience with large-scale model training, including data preparation and model parallelization.
  • Excellent programming skills in Python and PyTorch.
  • Outstanding research track record.
  • Excellent communications skills.
  • Background in pruning, quantization, NAS, and efficient backbones (preferred).
  • Proficiency in C++ and parallel programming, such as CUDA (preferred).

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