Role at a glance
- Salary
- $168K – $264.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- Outstanding research track record.
- Education
- Completing or recently completed a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or have equivalent research...
Spotted an issue?
We’ll check it against the original posting.
Role Summary
NVIDIA is hiring a researcher for its deep learning efficiency research team to develop efficient deep learning methods with potential impact on NVIDIA products. The role focuses on post-training model optimization, efficient architecture design, adaptive and dynamic inference, and resource-efficient training and finetuning, within a collaborative research environment.
What You'll Do
- 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
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience; excellent knowledge of computer vision methods and deep learning; experience with large language models and large vision-language models; excellent programming skills in Python and PyTorch; hands-on experience with large-scale model training, including data preparation and model parallelization; outstanding research track record; excellent communications skills.
Required
- Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., 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 and PyTorch
- Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline)
- Outstanding research track record
- Excellent communications skills
Preferred
- Background in pruning, quantization, NAS, efficient backbones, and so on
- C++ and parallel programming (e.g., CUDA)
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.