Nvidia Senior HPC Systems Engineer 

United States, Texas 

280935717

We are looking for an outstanding engineer for a Senior HPC Systems Engineer role for at scale AI system performance and datacenter applications. Be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing! Provide insights on at-scale system design 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 researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, CPU and GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms.

What you'll be doing:

• Lead all aspects of implementing performance practices in large scale infrastructure, deliver powerful tools, methodologies, and flows to validate and improve several datacenter products in parallel.

• Accelerate strategic customer deployments and ensure speed-of-light bringup and deployment of ground-breaking AI infrastructure by working hand in hand tailoring design and faster processes to customer needs.

• Provide engineering solutions to enable large scale performance strategies for performance for Datacenter GPU Computing products and software stacks, ensure technical relationships with internal and external engineering teams, and assisting systems engineers in building creative solutions based on NVIDIA technology.

• Participating in engagements with various SW and FW(BMC/SBIOS/OS/driversetc) teams to develop best-in-class practices and tools, you will be analyzing, debugging and resolving critical software issues for the best AI workload performance at scale.

• Specific responsibilities include owning the architecting of performance design and settings of datacenter at scale products both implemented in FW and SW components to ensure velocity and scale while efficiently using resources. This involves early engagement with HW/FW/SW/platform internal and customer teams, and other groups, to build end-to-end solutions and optimize datacenter product designs.

• Be an internal reference for software, at scale deployment for datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community.

What we need to see:

• 5+ years of experience in using accelerated computing for datacenter container computing solutions.

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

• Solid understanding of accelerated parallel computing models (MPI, NCCL).

• Experience using and handling modern Cloud and container-based Enterprise computing architectures.

• C/C++/Python/Bashprogramming/scriptingexperience.

• Experience with CPU architecture.

• Experience with container technology and Linux based OSes.

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

• Strong verbal and written communication skills as well as excellent teamwork and communication skills.

• Ability to multitask effectively in a dynamic environment.

Ways to Stand Out From the Crowd:

• Deep Learning framework skills.

• Hands-on experience with LLM training pipelines.

• Exposure to scheduling and resource management systems.

• Experience with large scale HPC environments.