Research Scientist, Efficient Deep Learning - New College Grad 2026

at Nvidia

USD 168,000-264,500 per year

JUNIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI CUDA @ 1 Communication @ 3 Computer Vision @ 7 Deep Learning @ 7 LLM Machine Learning Parallel Programming @ 1 PyTorch @ 3 Python @ 3

Details

NVIDIA is seeking an outstanding researcher to join the deep learning efficiency research team. The team focuses on research that pushes boundaries while having real-world impact, including post-training model optimization, pruning, quantization, neural architecture search (NAS), efficient architecture design, adaptive and dynamic inference, resource-efficient training, and fine-tuning. The team has expertise in computer vision, deep learning, and generative models, and its work is published at leading computer vision and machine learning venues.

Responsibilities

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

Requirements

Completing or recently completed a Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent research experience.
Excellent knowledge of the theory and practice of computer vision methods and deep learning.
Background in pruning, quantization, NAS, efficient backbones, or related areas is a plus.
Experience with large language models and large vision-language models is required.
Excellent programming skills in Python and PyTorch.
Experience with large-scale model training, including data preparation and tensor and pipeline model parallelization, is required.
Outstanding research track record.
Excellent communication skills.
Experience with C++ and parallel programming, such as CUDA, is a plus.

Benefits

Base salary range of $168,000–$264,500 USD per year, determined based on location, experience, and compensation for similar positions.
Eligible for equity and benefits.
NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until June 15, 2026.
NVIDIA uses AI tools in its recruiting processes.