NVIDIA 2027 Internships: Software Engineering
About The Position
NVIDIA is seeking strategic, ambitious, hard-working, and creative students for its 2027 Software Engineering internship opportunities. Interns gain hands-on experience with NVIDIA software teams and work on projects with measurable business impact during a 12-week, full-time internship. Potential areas include Development Tools, Cloud, Tools Infrastructure, and Machine Learning Operations. Work may involve debugging system-level issues; designing and supporting cloud storage infrastructure; building tools and workflows for production software development and chip design; enabling application tracing, modeling, diagnostics, performance tuning, and debugging; and developing infrastructure and frameworks for deep learning, GPU-accelerated computing, and backend analytics. Opportunities and specific requirements vary by internship role. Applications are reviewed on an ongoing basis, and this posting is for an existing vacancy.
Requirements
- Remain actively enrolled in a university and pursue a B.S., M.S., or Ph.D. in Electrical Engineering, Computer Engineering, or a related field for the full duration of the internship.
- Clearly indicate the anticipated graduation month and year on a resume or CV.
- Depending on the internship role, relevant coursework or internship experience may be required in areas such as relational databases, linear algebra and numerical methods, operating systems, distributed systems, data structures and algorithms, virtualization, automation and scripting, container and cluster management, or debugging.
- Depending on the internship role, experience or knowledge may be required in programming languages and technologies such as Java, JavaScript (including Node, React, or Vue), SQL, C, C++, CUDA, object-oriented programming, Go, Python, Git, Perforce, Kubernetes, microservices, LSF or SLURM schedulers, Docker, or Ansible.
Responsibilities
- Debug complex system-level issues using Jenkins in Development Tools roles.
- Support architecture and design of cloud storage infrastructure.
- Implement and troubleshoot storage and data platform tools and automate storage infrastructure end to end.
- Build workflows and infrastructure alongside teams working in production software development and chip design methodologies.
- Enable content running on chips through application tracing and analysis, modeling, diagnostics, performance tuning, and debugging.
- Work on deep learning, GPU computing, accelerated computing, validation frameworks, data preprocessing, training acceleration, convolution operations, real-time inference, or backend analytics, depending on the role.
Benefits
- Intern benefits are offered; specific benefits are not listed.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
