NVIDIA Spring 2027 Internships: Developer and Performance Technology

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 AWS @ 3 Automated Testing Azure @ 3 CUDA @ 3 Debugging @ 3 Deep Learning @ 3 Docker @ 3 GPU @ 3 HPC Kubernetes @ 3 LLM Linux @ 3 Marketing OpenCL @ 3 PyTorch @ 3 Python @ 3 Slurm @ 3 TensorFlow @ 3 TensorRT @ 3

Details

NVIDIA is seeking strategic, ambitious, hardworking, and creative students for 8–12-month, full-time internships in Developer and Performance Technology. Interns will gain hands-on experience with Deep Learning, accelerated computing, GPU technologies, and projects with measurable business impact.

Responsibilities

Performance Engineering

Run performance, image quality, and power tests for Professional Visualization, AI, and LLM benchmark applications on various GPUs.
Configure computer systems with the hardware and software required to run benchmarks.
Build automation scripts for benchmarking procedures and configuration files.
Assemble computer hardware, develop and run application automation scripts, and design tools.

Platform Performance and Power

Complete post-silicon performance and power benchmarking on NVIDIA and competitive GPU products.
Compile and analyze data for internal software, hardware, sales, and marketing teams.
Develop, implement, and maintain test systems by configuring hardware, operating systems, drivers, and benchmarking software.
Perform hands-on performance and power tests for GPU platforms.
Maintain automation tools to improve testing efficiency.

Deep Learning and High-Performance Computing

Plan and execute GPU performance benchmarks across HPC and deep learning frameworks and applications.
Aggregate, analyze, and report testing data in written and visual formats.
Write scripts to automate data gathering and design efficient testing processes for applications and hardware.
Assist with developing tools and processes to improve automated testing performance.

Requirements

Must be actively enrolled in a university and pursuing a B.S. or M.S. degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field for the full 8–12-month internship.
The anticipated graduation month and year must be clearly indicated on the resume or CV.
Preferred start dates are February 2027 or May 2027.
Relevant coursework or internship experience may include Linux, Unix and shell scripting, Python, GPU programming, GPU-accelerated deep learning frameworks, containers, embedded platforms, 3D graphics, benchmarking, debugging, image quality and power testing, and low-level system configuration.
Additional relevant technologies and tools include TensorFlow, PyTorch, MXNet, TensorRT, Torch, DML, CUDA, OpenCL, LAMMPS, GROMACS, Amber, RTM, AWS, Google Cloud Platform, Microsoft Azure, OpenACC, GNU Compiler Collection, Intel Composer, PGI, Slurm, Kubernetes, Docker, and Singularity.
Experience with electrical fundamentals, power measurement, multimeters, data acquisition tools, BIOS configuration, memory timing, cache latency control, and overclocking may be relevant depending on the internship role.

Benefits

Intern benefits are available.
NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.
Applications are reviewed on an ongoing basis.

Additional Information

By submitting a resume, applicants acknowledge that their application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and agree to NVIDIA’s Terms of Service. NVIDIA uses AI tools in its recruiting processes. This posting is for an existing vacancy.