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)
Click here to learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors.
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The expected hourly rate for this position 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.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
