Description

What you’ll be doing:

Provide engineering solutions to operationalize the latest GPU Computing products and software stacks, ensure technical relationships with internal and external engineering teams, and assisting systems, machine learning/deep learning engineers in building creative solutions based on NVIDIA technology.

Be an internal reference for system administration, at-scale system analysis, and other datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community.

What we need to see:

8+ years of experience using in accelerated computing for datacenter/HPC-based Enterprise computing solutions.

Solid understanding of accelerated computing scheduling and I/O stacks.

C/C++/Python/Bash programming/scripting experience.

Experience working with engineering or academic research community supporting high performance computing or deep learning.

Experience with parallel filesystems.

Strong teamwork and communication skills, both verbal and written.

Ability to multitask effectively in a dynamic environment.

Action driven with strong analytical skills.

Desire to be involved in multiple diverse and innovative projects.

BS (or equivalent experience) in Engineering, Mathematics, Physics, or Computer Science. MS or PhD desirable.

Ways to stand out from the crowd:

Deep Learning framework skills.

Exposure to using and deploying telemetry and visualization pipelines

Exposure to container technology and Linux performance tools

Key Skills

Education

Any Graduate