Developer and Performance Technology Intern

What you'll do

• Run performance, image quality, and power tests for AI and LLM benchmark applications on various GPUs.
• Configure computer systems with specific hardware and software to execute performance benchmarks.
• Build automation scripts to streamline benchmarking procedures and balance configuration files.
• Complete post-silicon performance and power benchmarking on NVIDIA and competitive GPU products.
• Compile and analyze data for internal software, hardware, sales, and marketing groups to inform business decisions.
• Develop, implement, and maintain test systems by configuring hardware, operating systems, drivers, and software tools.
• Plan and execute GPU performance benchmarking across a wide range of HPC and DL frameworks.
• Aggregate and generate written and visual reports containing testing data for internal teams.

What we're looking for

• Must be actively enrolled in a university pursuing a B.S. or M.S. degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Must be available for the full 8–12-month duration of the internship.
• Must clearly indicate an anticipated graduation date (month and year) on the resume or CV.
• Course or internship experience in Linux, Python/Unix Shell Scripting, and Debugging may be required.
• Course or internship experience in GPU Accelerated Deep Learning Frameworks (TensorFlow, PyTorch, MXNet, TensorRT, Torch, DML) may be required.
• Course or internship experience in GPU Programming (CUDA, OpenCL) may be required.
• Course or internship experience in Containers (Docker or Singularity) may be required.
• Course or internship experience in various technical areas including 3D Graphics, Benchmarking, and Electrical Fundamentals may be required.