Research Scientist, Efficient Deep Learning - New College Grad 2026

Reposted 28 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
168K-265K Annually
Entry level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Conduct research and implement novel methods for efficient deep learning (pruning, quantization, NAS, adaptive inference, resource-efficient training). Publish results, collaborate across teams, mentor interns, present at conferences, and help transfer research into NVIDIA products.
Summary Generated by Built In

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.

Skills Required

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

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 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, NVIDIA is increasingly known as “the AI computing company.”

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