Software Engineer, Deep Learning Libraries - New College Graduate 2026

NVIDIA•Santa Clara, CA

1d•$124,000 - $241,500

About The Position

NVIDIA's Deep Learning Libraries Team is looking for excellent software engineers to enable the next wave of NVIDIA’s highest performing deep learning software. The mission is to design and develop scalable and modular software products that enable breakthroughs in problems from image classification to speech recognition to natural language processing and artificial intelligence. Join the team which is building software which will be used by the entire world.

Requirements

Strong programming skills in C/C++
Pragmatic approach to solving problems and collaboration
Experience in SCM (e.g., Git, Perforce) and build systems (e.g., Make, CMake, Bazel)
Passion for “it just works” automation and enabling team members
The ability to work independently, define project goals and scope, and lead your own development effort.
Graduating with a BS, MS or PhD in Computer Science, Compute Engineering or similar (or equivalent experience)

Nice To Haves

Knowledge of CPU and/or GPU architecture.
CUDA or OpenCL programming experience strongly desired
Experience in optimizing for high performance computing, linear algebra algorithms and parallel implementations.
Experience in compiler optimizations
Experience with code coverage and static code analysis tools

Responsibilities

Develop and deliver highly optimized deep learning products.
Define public APIs.
Performance tuning and analysis.
Build developer infrastructure.
Testing automation.
Join architecture discussions.
Learn latest and greatest technologies from the research community.
Design and develop robust and scalable GPU-accelerated deep learning libraries, using C++ and object-oriented design.
Build scalable automation for build, test, integration, and release processes for publicly distributed deep learning libraries.
Maintain and test environments for new hardware, new OSes, and platforms by using industry-standard tools (e.g., Kubernetes, Jenkins, Docker, CMake, Gitlab, Jira, etc).
Participate in a high-energy and dynamic company culture to develop state of the art software and hardware products and practice hardware-software co-design.