About the role#
NVIDIA is looking for Ph.D. students to join our Graphics and Simulation research teams. This is a full-time, paid internship based in Santa Clara. We review applications on a rolling basis throughout the year.
What you'll do#
- Design and develop algorithms, hardware, and software for graphics and simulation.
- Invent new techniques and methodologies to enable new products.
- Create prototypes and contribute to patents.
- Collaborate with internal teams and external researchers to advance computing and media processing.
What you'll need#
- Active enrollment in a Ph.D. program for Computer Science, Electrical Engineering, Physics, Mathematics, or Data Science.
- A strong research background with publications at top conferences.
- Programming proficiency in Python, C, and CUDA.
- Excellent communication skills for collaborative work.
- Experience with large-scale model training is a plus.
Location & details#
- Location: Santa Clara, California, United States.
- Modality: On-site.
- Compensation: 38 USD - 94 USD per hour, depending on experience and degree level.
- Note: Sponsorship is not provided for this role.
About NVIDIA
NVIDIA operates as a computer hardware manufacturer based in Santa Clara, California. Founded in 1993, the company focuses on accelerated computing and graphics technology. It produces hardware for markets including artificial intelligence, gaming, and data centers. The organization employs over 50,000 people and maintains a global presence.
How to get in at NVIDIA
Applying early gives you a distinct advantage at NVIDIA because recruiters review applications as they arrive. Intern Insider sends an instant alert the moment a role matching your target is published, so you can apply among the first before the pile grows. Getting your resume in front of a human early is often the difference between a screening call and a rejection. You can use Intern Insider to surface the recruiters behind NVIDIA roles to reach out directly. Asking a recruiter about the role or a referral materially improves your response rates compared to submitting into a general queue. It is a simple way to make your application stand out in a competitive process.
