PhD Researcher in Generative AI Internship

Nvidia Corporation; Santa Clara (CA); On-site; USD 52,000 - 129,000; Full time

Job summary

NVIDIA is seeking PhD students for internships to design and implement algorithms advancing generative AI, computer vision, robotics, and related areas. You will collaborate with researchers and translate research into tangible outputs for product teams, producing prototypes, publications, or patents as part of ongoing projects.

Strong publication records, excellent communication, and teamwork skills are required, with experience in large-scale model training considered a plus.

Qualifications

• Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for the full duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered.
• Proficiency in Python/C++ with CUDA and deep learning frameworks (PyTorch, JAX, TensorFlow, etc.).
• Strong background in research with publications at top conferences.
• Excellent communication and collaboration skills.
• Experience with large-scale model training is a plus.

Responsibilities

• Design and implement algorithms that push the boundaries of generative AI, computer vision, robotics, and related domains.
• Collaborate with other team members, teams, and external researchers.
• Transfer research results to product groups to enable new products; deliverables may include prototypes, patents, products, and/or publishing original research.

Skills

Python

C++

CUDA

PyTorch

JAX

TensorFlow

Research publications

Communication

Collaboration

Model training

Education

PhD in CS/EE

Job description

NVIDIA is seeking PhD students for internships to design and implement algorithms advancing generative AI, computer vision, robotics, and related areas. You will collaborate with researchers and translate research into tangible outputs for product teams, producing prototypes, publications, or patents as part of ongoing projects.

Strong publication records, excellent communication, and teamwork skills are required, with experience in large-scale model training considered a plus.