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 you agree to our Terms of Service. We'll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.
Throughout the 12-week full-time internship, students will work on projects that have a measurable impact on our business. We're looking for students pursuing a B.S., M.S., or Ph.D. degree within a relevant or related field.
Potential Internships in this field include: Development Tools
- Debugging complex system-level issues using Jenkins
- Course or internship experience related to the following areas could be required: Relational Databases, Linear Algebra & Numerical Methods, Operating Systems (memory/resource management), Scheduling and Process Control, Hardware Virtualization
Cloud
- Supporting overall architecture and design of our cloud storage infrastructure
- Implementing and troubleshooting storage and data platform tools, automating storage infrastructure end-to-end
- Course or internship experience related to the following areas could be required: Distributed Systems, Data Structures & Algorithms, Virtualization, Automation/Scripting, Container & Cluster Management, Debugging
Tools Infrastructure
- Building industry leading technology by proving workflows and infrastructure, alongside a team of experts in production software development and chip design methodologies
- Enabling success for content running on the chip from application tracing and analysis to modeling, diagnostics, performance tuning, and debugging
- Course or internship experience related to the following areas and technologies could be required: Unix/Shell Scripting, Linux, Java, JavaScript (including Node, React, Vue), C++, CUDA, OOP, Go, Python, Git, GitLab, Perforce, Kubernetes and Microservices, Schedulers (LSF, SLURM), Containers (Docker), Configuration Automation (Ansible)
Machine Learning Operations
- Deep Learning, GPU Computing, Accelerated Computing
- Validation Frameworks for Deep Learning, Deep Learning Frameworks and Libraries (NumPy, SciPy, cuBLAS, cuDNN)
- Data Preprocessing, Training Acceleration (CUDA, cuDNN, NCCL), Convolution Operations (cuDNN), Real-Time Inference (TensorRT)
- Building Infrastructure for Back-End Analytics
What we need to see: - Must be 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 a resume or CV to be considered.
- Depending on the internship role, prior experience or knowledge requirements could include the following programming skills and technologies: Java, JavaScript, (including Node, React, Vue), SQL, C, C++, CUDA, OOP, Go, Python, Git, Perforce, Kubernetes and Microservices, Schedulers (LSF, SLURM), Containers (Docker), Configuration Automation (Ansible)
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Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.
You will also be eligible for Intern benefits.
Applications are accepted on an ongoing basis.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
