Nvidia Senior Solution Architect HPC AI - NVIS 

United States, Texas 

475924318

What You’ll Be Doing:

• Primary responsibilities will include building and enabling robust AI/HPC infrastructure for customers

• Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, training stability, real-time monitoring, logging, and alerting

• Engage in and improve services from inception and design through deployment, operation, and optimization

• Co-design telemetry of AI workloads to help engineering build solutions for more robust workloads at scale

• Communicate across internal teams to support the continuous improvement of NVIDIA's offerings and software designs

What We Need to See:

• Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).

• 8+ years of experience and knowledge of neural networks including good understanding of transformer architectures. Experience designing large scale AI workloads with SLURM and/or Kubernetes

• Proficiency with Python / C++ / Rust or other popular software languages

• Excellent verbal, written communication, and technical presentation skills in English

• You are motivated to work with multiple levels and teams across organizations

• Strong analytical and problem-solving skills

• Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects

• You are a curious self-starter with a desire for continuous learning and sharing knowledge across the team

Ways to Stand Out from The Crowd:

• Experience orchestrating distributed Deep Learning training with SLURM

• Proficiency in DevOps, including hands-on experience with Ansible, Terraform or similar tools. Equivalent experience will be accepted as well.

• 8+ years designing solutions with one or more Tier-1 Clouds (AWS, Azure, GCP or OCI) and cloud-native architectures and software

• Technical leadership with a strong understanding of NVIDIA technologies, and success in working with customers

• Expertise with parallel file systems (e.g. Lustre, GPFS, BeeGFS, WekaIO) and high-speed interconnects (InfiniBand, Omni Path, and Gig-E)

• Experience with integration and deployment of software products in production enterprise environments, and microservices software architecture