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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
896 open roles
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Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
NVIDIA Spring 2027 Internships: Developer and Performance Technology offers students pursuing a B.S. or M.S. in relevant fields the opportunity to join Deep Learning teams for an eight-to-twelve-month internship. Candidates will work on projects involving performance engineering, platform performance and power, or deep learning and high-performance computing. Daily responsibilities include running performance, image quality, and power tests for AI and LLM benchmarks; building automation scripts; configuring hardware and software systems; and analyzing data to inform internal decisions. Required technical skills include Linux, Python, and Shell Scripting, alongside specialized knowledge in GPU programming via CUDA or OpenCL. Candidates may also utilize frameworks like PyTorch, TensorFlow, and TensorRT, along with tools such as Docker, Slurm, and Kubernetes. The work focuses on solving complex challenges in accelerated computing for AI and high-performance computing applications.
Run performance, image quality, and power tests for Professional Visualization, AI, and LLM benchmark applications on various GPUs.
Configure computer systems with specific hardware and software to execute benchmarking procedures.
Build automation scripts to streamline benchmarking processes and manage configuration files.
Perform post-silicon performance and power benchmarking on NVIDIA and competitive GPU products.
Compile and analyze testing data to inform decisions for internal software, hardware, sales, and marketing teams.
Develop, implement, and maintain test systems by configuring operating systems, drivers, and software tools.
Execute GPU performance benchmarking across a wide range of HPC and Deep Learning frameworks.
Create automated scripts and design efficient processes to improve the performance of automated testing.
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.
Candidates must provide an anticipated graduation date (month and year) on their resume or CV.
Experience with GPU Accelerated Deep Learning Frameworks (TensorFlow, PyTorch, MXNet, TensorRT, Torch, DML) is required for some roles.
Experience with GPU Programming (CUDA, OpenCL) is required for some roles.
Experience with Linux and Python/Unix Shell Scripting is required for some roles.
Experience with Containers (Docker or Singularity) is required for some roles.
Knowledge of 3D Graphics, Image Quality and Power Testing, Low Level System Configuration, or Electrical Fundamentals may be required depending on the role.
Knowledge of HPC Applications, Compilers, Clusters, or Embedded Platforms may be required depending on the role.
Deep Learning
CUDA
PyTorch
TensorFlow
JAX
cuDNN
cuBLAS
C++
C
Python
GPU Programming
High-Performance Computing
Linux
Docker
Kubernetes
Spark
Kafka
Cassandra
OpenCL
Vulkan
OpenGL
Direct3D
Bash
Go
C
C++
CUDA
Linux Kernel Development
RTOS
x86
ARM
GPU
Bash
Shell Scripting
OpenGL
Vulkan
Clang
GCC
XLA
TVM
Halide
High-Performance Computing
Embedded Systems
Perl
CUDA
C++
C
Python
GPU Architecture
CPU Architecture
Operating Systems
Distributed Systems
AI
Parallel Computing
Compilers
VLSI
EDA
High-Performance Networking
Hardware-Software Co-design
LLM Training
Memory Systems