Research Scientist, Efficient Deep Learning - New College Grad 2026
at Nvidia
USD 168,000-264,500 per year
Used Tools & Technologies
LLMRequired Skills & Competences
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.
Python @ 3
Machine Learning @ 3
Communication @ 3
Parallel Programming @ 3
PyTorch @ 3
CUDA @ 3
Deep Learning @ 3
AI @ 3
Computer Vision @ 3
- 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.
Details
NVIDIA is searching for an outstanding researcher working on efficient deep learning to join the deep learning efficiency research team. The team focuses on research that pushes boundaries and has real-world impact. Areas of interest include post-training model optimization (pruning, quantization, NAS), efficient architecture design, adaptive/dynamic inference, resource-efficient training and finetuning, and related topics. You will work within a collaborative research team that publishes at top venues in computer vision and machine learning and has expertise in computer vision, deep learning, and generative models.
Responsibilities
- Research, design and implement novel methods for efficient deep learning.
- Publish original research at top conferences and venues.
- Collaborate with other team members and cross-functional teams.
- Mentor interns.
- Speak at conferences and events.
- Work with product groups to transfer technology into products.
- Collaborate with external researchers.
Requirements
- Completing or recently completed a Ph.D. in Computer Science/Engineering, 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 is required.
- Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.
- Excellent programming skills in Python and PyTorch; C++ and parallel programming (e.g., CUDA) are a plus.
- Background in pruning, quantization, NAS, efficient backbones, and related methods is a plus.
- Outstanding research track record and excellent communication skills.
Compensation & Benefits
- Base salary range: 168,000 USD - 264,500 USD (determined based on location, experience, and pay of employees in similar positions).
- Eligible for equity and additional benefits.
Additional information
- Applications for this job will be accepted at least until June 15, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering an inclusive work environment.