Description

Operationalize GPU computing products and software stacks while supporting system, machine learning, and deep learning engineers in building scalable, GPU-accelerated solutions.

This role is on-site.

Responsibilities

• Provide engineering solutions to operationalize the latest GPU Computing products and software stacks.
• Maintain technical relationships with internal and external engineering teams.
• Support systems, machine learning, and deep learning engineers in building creative solutions based on NVIDIA technology.
• Serve as the internal reference for system administration, at-scale system analysis, and large-scale GPU-accelerated system solutions.

Required Skills

• 8+ years of experience in accelerated computing for datacenter/HPC-based Enterprise computing solutions.
• Strong understanding of accelerated computing scheduling and I/O stacks.
• Proficiency in C/C++, Python, and Bash programming/scripting.
• Experience working with engineering or academic research communities supporting high performance computing or deep learning.
• Experience with parallel filesystems.
• BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience).
• Strong analytical, multitasking, and communication skills.

Preferred Skills

• Deep Learning framework skills.
• Exposure to telemetry and visualization pipelines.
• Experience with container technology and Linux performance tools.

Key Skills

Education

Any Graduate