GPU-Accelerated Deep Learning Library Engineer

NVIDIA Gruppe; Santa Clara (CA); On-site; USD 124,000 - 242,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA's Deep Learning Libraries Team seeks software engineers to design and develop scalable GPU-accelerated deep learning libraries for breakthroughs in image, speech, NLP and AI. You will build automation for builds, tests, integration, and releases, and maintain environments for new hardware and OSes using Kubernetes, Jenkins, Docker, CMake, GitLab, Jira, etc.

This role offers wide impact across NVIDIA's software and hardware stack, with equity and benefits; base salary varies by location

Qualifications

• Design and develop GPU-accelerated deep learning libraries in C++.
• Demonstrates pragmatic problem solving and collaboration.
• Experience with SCM and common build systems.
• Passion for automation and enabling teammates.
• Ability to work independently and lead development efforts.
• Graduated with BS/MS/PhD in CS/Compute Eng or equivalent

Responsibilities

• Design and develop robust GPU-accelerated deep learning libraries using C++ and OO design.
• Build scalable automation for build, test, integration, and release processes.
• Maintain and test environments for new hardware/OS with industry tools.
• Collaborate in a high-energy culture to co-design software and hardware.

Skills

C/C++ programming

Git/Perforce

Build systems

Education

BS/MS/PhD in CS/Compute Eng

Tools

Kubernetes

Jenkins

Docker

CMake

GitLab

Jira

Job description

NVIDIA's Deep Learning Libraries Team seeks software engineers to design and develop scalable GPU-accelerated deep learning libraries for breakthroughs in image, speech, NLP and AI. You will build automation for builds, tests, integration, and releases, and maintain environments for new hardware and OSes using Kubernetes, Jenkins, Docker, CMake, GitLab, Jira, etc.

This role offers wide impact across NVIDIA's software and hardware stack, with equity and benefits; base salary varies by location