NVIDIA Spring 2027 Internships: Developer and Performance Technology

NVIDIA offers an 8-12 month full-time internship program for students pursuing a B.S. or M.S. degree in a relevant field. As an intern, you will work on projects with a measurable impact on the business, focusing on Performance Engineering, Platform Performance and Power, or Deep Learning and High-Performance Computing (HPC).

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 appropriate hardware and software to run benchmarks.
• Build automation scripts to streamline benchmarking procedures.

• Platform Performance and Power:
• Complete post-silicon performance and power benchmarking on NVIDIA and competitive GPU products.
• Develop, implement, and maintain test systems for benchmarking and data collection.

• Deep Learning and High-Performance Computing (HPC):
• Plan and execute GPU performance benchmarking across various HPC and DL Frameworks and Applications.
• Write scripts to improve data gathering through automation.

Requirements:

• Actively enrolled in a university pursuing a B.S. or M.S. degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Anticipated graduation date must be clearly indicated on a resume or CV.
• Preferred start dates: February 2027 or May 2027.

Benefits:

• Hourly rates: $20-$71 per hour, depending on position, location, year in school, degree, and experience.
• Eligibility for Intern benefits.

Skills:

• Programming skills: Python, C++, Java, etc.
• Familiarity with GPU Accelerated Deep Learning Frameworks (TensorFlow, PyTorch, MXNet, TensorRT), GPU Programming (CUDA, OpenCL), HPC Applications (LAMMPS, GROMACS, Amber, RTM), Linux, Python/Unix Shell Scripting, Containers (Docker or Singularity).
• Knowledge of 3D Graphics, Image Quality and Power Testing, Low Level System Configuration, Electrical Fundamentals, Compilers, Clusters, Embedded Platforms, Debugging, Benchmarking, Power Testing.