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 @ 3
Algorithms
CUDA @ 3
Communication @ 3
Computer Vision
Deep Learning @ 3
GenAI
Generative AI @ 3
JAX @ 3
LLM
PyTorch @ 3
Python @ 3
Robotics
TensorFlow @ 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
By submitting your resume, you acknowledge that your Ph.D. Research Generative AI internship application will be processed in accordance with NVIDIA's Applicant Privacy Policy and agree to NVIDIA's Terms of Service. Resumes will be reviewed on an ongoing basis, and a recruiter may reach out if your experience fits one of the internship opportunities.
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Its work in AI and digital twins is transforming industries and impacting areas including gaming, robotics, self-driving cars, healthcare, climate change, and virtual worlds.
These internships provide an opportunity to gain hands-on experience with NVIDIA's Generative AI teams. NVIDIA seeks strategic, ambitious, hardworking, collaborative, and creative individuals who are passionate about solving challenging problems.
Responsibilities
- Design and implement algorithms that advance generative AI, computer vision, robotics, and other technology domains relevant to NVIDIA's business.
- Collaborate with team members, other teams, and external researchers.
- Transfer research to product groups to enable new products or product categories.
- Deliver results such as prototypes, patents, products, and/or original research publications.
Requirements
- Actively enrolled in a university Ph.D. program in Computer Science, Electrical Engineering, or a related field for the full duration of the internship.
- Clearly indicate the anticipated graduation month and year on your resume or CV.
- Depending on the internship, prior experience or knowledge may include Python, C++, CUDA, and deep learning frameworks such as PyTorch, JAX, or TensorFlow.
- Strong research background with publications at top conferences.
- Excellent communication and collaboration skills.
- Experience with large-scale model training is a plus.
Potential internships require research experience in at least one of the following areas:
- Multimodal foundation models
- Diffusion models
- World models
- Image, video, or audio generation
- Large language models
- Vision-language models
- Action-based transformers
- Long-context methods
- Physics-based simulation
- Flow-based generative models
- Synthetic data generation
- AI for science
- Protein or molecule generation
- Climate modeling and weather forecasting
- Partial differential equations (PDEs)
Compensation and Benefits
The standard intern hourly rate is based on the position, location, year in school, degree, and experience. The hourly rate is USD 38–94. Interns are also eligible for benefits.
Applications are accepted on an ongoing basis. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to an inclusive work environment.