About the role#
This internship offers a 12-week, full-time opportunity to contribute to deep learning, data analytics, or scientific computing projects. You will work directly with teams focused on GPU implementations and software frameworks. We review applications on a rolling basis throughout the year.
What you'll do#
- Develop and optimize algorithms for deep learning and scientific computing.
- Improve the performance of GPU implementations.
- Build and maintain underlying frameworks and libraries to accelerate deep learning on GPUs.
- Contribute to software packages including JAX, PyTorch, and TensorFlow.
- Integrate new library features and perform tuning and analysis.
- Manage build, test, and distribution infrastructure for deep learning libraries.
What you'll need#
- Active enrollment in a B.S., M.S., or Ph.D. program in Electrical Engineering, Computer Engineering, or a related field for the duration of the internship.
- A resume or CV that clearly indicates your anticipated graduation date.
- Course or internship experience in at least one of the following: Deep Neural Networks, Linear Algebra, Numerical Methods, or Computer Vision.
- Background in software design, computer memory, CPU and GPU architectures, or networking.
- Exposure to numeric libraries, embedded system design, drivers, or real-time software.
- Understanding of GPU programming models, parallel programming, or high-performance computing optimization.
Location & details#
- Location: Santa Clara, California.
- Modality: On-site.
- Duration: 12 weeks, full-time.
- Compensation: Paid internship with hourly rates ranging from 20 USD to 71 USD, depending on experience and education level.
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.
