NVIDIA 2027 Internships: Deep Learning
$0k - $0k • Remote • US, CA, Santa Clara
Posted 7d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
NVIDIA is seeking strategic, ambitious, hard-working, and creative individuals for its 2027 Deep Learning internship program. This 12-week full-time internship offers an excellent opportunity to expand your career and gain hands-on experience with industry-leading Deep Learning teams. Interns will work on projects with a measurable impact on NVIDIA's business, contributing to advancements in AI and digital twins that are transforming major industries. We are looking for students pursuing a B.S., M.S., or Ph.D. degree in a relevant field who are passionate about tackling complex challenges.
Responsibilities
- Develop algorithms for deep learning, data analytics, or scientific computing to improve GPU implementation performance.
- Build underlying frameworks and libraries to accelerate Deep Learning on GPUs.
- Contribute to software packages like JAX, PyTorch, and TensorFlow, integrating new features, and performing performance tuning and analysis.
- Optimize core deep learning algorithms and libraries, and maintain build, test, and distribution infrastructure for these libraries and frameworks on NVIDIA platforms.
Requirements
- Actively enrolled in a university pursuing a B.S., M.S., or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field for the full duration of the internship.
- Anticipated graduation date (month and year) must be clearly indicated on resume or CV.
- Course or internship experience related to Deep Neural Networks, Linear Algebra, Numerical Methods, Computer Vision, Software Design, Computer Memory, CPU and GPU Architectures, Networking, Numeric Libraries, Embedded System Design and Development, Drivers, or Real-Time Software may be required.
- Course or internship experience related to Computer Architecture (CPUs, GPUs, FPGAs or other accelerators), GPU Programming Models, Performance-Oriented Parallel Programming, Optimizing for High-Performance Computing (HPC), Algorithms, or Numerical Methods may be required.
- Prior experience or knowledge in programming skills and technologies such as C, C++, CUDA, Python, x86, ARM CPU, GPU, Linux, Direct3D, Vulkan, OpenGL, OpenCL, Spark, Perl, Bash/Shell Scripting, Container Tools (Docker/Containers, Kubernetes), Infrastructure Platforms (AWS, Azure, GCP), Data Technologies (Kafka, ELK, Cassandra, Apache Spark), React, or Go may be required depending on the specific role.
Benefits
- Intern benefits eligibility
- Internship hourly rates are standardized based on position, location, year in school, degree, and experience.