NVIDIA 2027 Internships: Deep Learning

Details

By submitting a resume, applicants acknowledge that their 2027 Deep Learning internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and agree to NVIDIA’s Terms of Service. Resumes are reviewed on an ongoing basis, and a recruiter may reach out if an applicant’s experience fits one of NVIDIA’s internship opportunities.

NVIDIA pioneered accelerated computing to tackle challenges that no one else can solve. Its work in AI and digital twins is transforming industries including gaming, robotics, self-driving cars, healthcare, climate technology, and virtual worlds. This internship provides hands-on experience with NVIDIA’s Deep Learning teams.

The 12-week, full-time internship offers students the opportunity to work on projects with a measurable business impact. NVIDIA is seeking students pursuing a B.S., M.S., or Ph.D. degree in a relevant or related field.

Potential Internship Areas

Deep Learning Applications and Algorithms

• Develop algorithms for deep learning, data analytics, or scientific computing to improve the performance of GPU implementations.
• Relevant course or internship experience may include deep neural networks, linear algebra, numerical methods, computer vision, software design, computer memory including disks, memory, and caches, CPU and GPU architectures, networking, numeric libraries, embedded system design and development, drivers, and real-time software.

Deep Learning Frameworks and Libraries

• Build underlying frameworks and libraries to accelerate deep learning on GPUs.
• Contribute to software packages such as JAX, PyTorch, and TensorFlow.
• Integrate the latest library features, such as cuDNN, and CUDA features.
• Perform performance tuning and analysis.
• Optimize core deep learning algorithms and libraries such as cuDNN and cuBLAS.
• Maintain build, test, and distribution infrastructure for deep learning libraries and frameworks on NVIDIA-supported platforms.
• Relevant course or internship experience may include computer architecture involving CPUs, GPUs, FPGAs, or other accelerators; GPU programming models; performance-oriented parallel programming; high-performance computing; algorithms; and numerical methods.

Requirements

• Applicants must be actively enrolled at a university and 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.
• The anticipated graduation month and year must be clearly indicated on the resume or CV.
• Depending on the internship role, prior experience or knowledge may include C, C++, CUDA, Python, x86, ARM CPUs, GPUs, Linux, Direct3D, Vulkan, OpenGL, OpenCL, Spark, Perl, Bash or shell scripting, Docker or other container tools, Kubernetes, AWS, Azure, GCP, Kafka, ELK, Cassandra, Apache Spark, React, and Go.

Internship Details

• Duration: 12 weeks
• Schedule: Full time
• Applications are accepted on an ongoing basis.
• The posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.

Compensation and Benefits

• Hourly rate: USD 20–71, based on the position, location, year in school, degree, and experience.
• Intern benefits are available.