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Research Scientist, Efficient Deep Learning - New College Grad 2026

NVIDIA
Posted 3 months ago, valid for 10 days
Location

Santa Clara, CA 95052, US

Salary

$168,000 - $264,500 per year

Contract type

Full Time

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Sonic Summary

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  • NVIDIA is seeking a researcher in efficient deep learning to join their deep learning efficiency research team.
  • Candidates should have a Ph.D. in Computer Science, Engineering, or a related field, along with experience in large language models and deep learning.
  • The position involves researching and implementing methods for efficient deep learning, publishing original research, and collaborating with team members and external researchers.
  • The base salary for this role ranges from 168,000 USD to 264,500 USD, depending on location and experience.
  • NVIDIA values diversity and is committed to creating an inclusive work environment, accepting applications until at least June 15, 2026.

NVIDIA is searching for an outstanding researcher working on efficient deep learning to join the deep learning efficiency research team. We are passionate about research that pushes boundaries but also has impact in the real world. We are particularly excited about methods for post-training model optimization (pruning, quantization, NAS), efficient architecture design, adaptive/dynamic inference, resource-efficient training and finetuning, and so forth. You will work within an amazing and collaborative research team that consistently publishes at the top venues in computer vision and machine learning. Our existing expertise includes computer vision, deep learning, generative models, and so forth. Your contributions have the chance to create real impact on our products.

What you'll be doing:

  • 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.

What we need to see:

  • 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 a plus.

  • Experience with large language models and large vision-language models is required.

  • 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.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 15, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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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By applying, a NVIDIA account will be created for you. NVIDIA's Privacy Policy and Terms & Conditions will apply.

SonicJobs' Terms & Conditions and Privacy Policy also apply.