NVIDIA 2027 Internships: Software Engineering

at Nvidia

USD 20-71 per hour

INTERN

✅ On-site

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 Algorithms @ 3 Ansible @ 3 CUDA @ 3 Data Structures @ 3 Debugging @ 3 Deep Learning Distributed Systems @ 3 Docker @ 3 GPU Git @ 3 Go @ 3 Java @ 3 JavaScript @ 3 Jenkins Kubernetes @ 3 Linux @ 3 Machine Learning Microservices @ 3 NCCL Node.js @ 3 Python @ 3 React @ 3 Robotics SQL @ 3 Slurm @ 3 TensorRT

Details

By submitting your resume, you acknowledge that your 2027 Software Engineering internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and Terms of Service. Resumes will be reviewed on an ongoing basis, and a recruiter may reach out if your experience fits one of NVIDIA’s 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 hands-on experience with NVIDIA’s software teams.

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

Potential Internship Areas

Development Tools

Debug complex system-level issues using Jenkins.
Relevant coursework or internship experience may include relational databases, linear algebra and numerical methods, operating systems, memory and resource management, scheduling and process control, and hardware virtualization.

Cloud

Support the architecture and design of cloud storage infrastructure.
Implement and troubleshoot storage and data platform tools.
Automate storage infrastructure end to end.
Relevant coursework or internship experience may include distributed systems, data structures and algorithms, virtualization, automation and scripting, container and cluster management, and debugging.

Tools Infrastructure

Build technology by improving workflows and infrastructure alongside experts in production software development and chip design methodologies.
Enable content running on chips through application tracing and analysis, modeling, diagnostics, performance tuning, and debugging.
Relevant coursework or internship experience may include Unix and shell scripting, Linux, Java, JavaScript including Node.js, React, and Vue, C++, CUDA, object-oriented programming, Go, Python, Git, GitLab, Perforce, Kubernetes, microservices, LSF, SLURM, Docker, and Ansible.

Machine Learning Operations

Work with deep learning, GPU computing, and accelerated computing.
Use validation frameworks for deep learning and libraries including NumPy, SciPy, cuBLAS, and cuDNN.
Work with data preprocessing, training acceleration using CUDA, cuDNN, and NCCL, convolution operations using cuDNN, and real-time inference using TensorRT.
Build infrastructure for back-end analytics.

Requirements

Must be actively enrolled in 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 date, including month and year, must be clearly indicated on the resume or CV.
Depending on the internship role, prior experience or knowledge may be required in Java, JavaScript including Node.js, React, and Vue, SQL, C, C++, CUDA, object-oriented programming, Go, Python, Git, Perforce, Kubernetes, microservices, LSF, SLURM, Docker, and Ansible.

Compensation and Benefits

Internship hourly rates range from USD 20 to USD 71, depending on the position, location, year in school, degree, and experience.
Interns are eligible for NVIDIA’s intern benefits.
Applications are accepted on an ongoing basis.

NVIDIA uses AI tools in its recruiting processes and is committed to fostering an inclusive work environment and providing equal employment opportunities.