We are now seeking a Senior AI Infrastructure Engineer! NVIDIA’s Compute Architecture Group is growing our team of AI focused Infrastructure Engineers who run our internal cluster for accelerated AI and software development. As part of this team, you will help to manage a diverse cluster of GPU-accelerated systems. Your contributions will enable engineers to work efficiently with a wide variety of forward-looking hardware configurations as they vigilantly seek out opportunities for performance optimization and continuously deliver high quality software.

Our ideal candidate is versatile enough to apply expertise from many domains: system administration, performance analysis, automation, and architecture. Your work will enable the ground breaking experimentation that allows us to design the world’s most powerful systems for the most demanding computing applications. You will have a meaningful impact at a fast-moving company that is spearheading the next wave in computing technology. Join our technically diverse team of GPU architects, software engineers and infrastructure experts to unlock unprecedented performance in every domain!

What you'll be doing:

• Administer an NVIDIA Internal AI cluster composed of Linux systems ranging from the world’s most powerful servers to embedded systems

• Maintain the configuration of our resource management system (SLURM) to keep resource allocation efficient and aligned with organizational priorities

• Automate configuration management, software updates, and maintenance of system availability using modern DevOps tools (Ansible, Gitlab, etc.)

• Plan and maintain new systems that support the NVIDIA Software stack

• Work directly with developers and hardware architects to debug issues, identify new requirements, and improve workflows

• Actively communicate with users and management regarding resource planning and allocation

What we need to see:

• 5+ years of previous experience deploying and administering large scale clusters, tuned for development efforts in AI

• MS in Computer Science, Computer Engineering, or EECE; or a BS (or equivalent experience).

• Deep knowledge of distributed resource scheduling systems (Slurm (preferred), LSF, etc.)

• Demonstrated ability to script in bash, and at least one high-level language (Python preferred)

• Experience with container technologies (Docker, Singularity, etc.)

• Deep understanding of operating systems, computer networks, and high-performance hardware

• Ability to work well with developers, hardware architects, & test engineers

• Passionate dedication to providing quality support for users

Ways to stand out from the crowd:

• Prior work experience managing high performance fabrics and parallel file systems

• Familiarity with CUDA and managing GPU-accelerated computing systems

• Basic knowledge of deep learning frameworks and algorithms

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.