Senior HPC Architect

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today**!**

We are looking for an outstanding hands-on architect/engineer for a Senior HPC architect role to support deployment and bringup of large-scale GPU compute clusters. Be a key player to enable the most exciting computing hardware and software and contribute to the latest breakthroughs in artificial intelligence and GPU computing. Provide insights on and implement at-scale system administration and tuning mechanisms for large-scale compute runs. You will work with the latest accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms.

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.