AI GPU Platform Engineering

Role Summary

AI GPU Platform Engineering role focusing on AI/HPC infrastructure, Nvidia DGX server management, Spectrum X networking, and WEKA storage integration to support AI/ML workloads. Located in Indianapolis, IN with hybrid work and relocation required.

Responsibilities

• Drive the engineering and operations of advanced Linux platforms supporting AI and HPC workloads.
• Manage Nvidia DGX systems using Mission Control, Base Command, and Run:AI.
• Optimize Spectrum X networking and WEKA storage for AI/ML applications.
• Improve productivity for Advanced Intelligence and Data Science teams through AI/HPC infrastructure tooling and operational excellence.
• Lead strategy, engineering, and development of Advanced Linux computing capabilities for AI/ML within the Infrastructure Hosting Platform.
• Advise with the senior Linux platform engineer on global Linux strategy for on-premises private cloud and public IaaS Linux services.

Qualifications

• Required: 10+ years of experience as a Linux OS/Platform Engineer; Bachelor's degree in computer science, IT, or related field.
• Preferred: 6+ years of demonstrated experience in AI/ML and HPC workloads; experience leading global large-scale infrastructure projects.
• Expertise in Linux system administration, HPC environments, and Nvidia DGX server management; Spectrum X networking and parallel file systems.
• Strong scripting skills; familiarity with containerization and automation tools.
• Hands-on experience with HPC infrastructure, accelerated computing (GPU), storage (WEKA), scheduling/orchestration (Slurm, Kubernetes, LSF), high-speed networking (Ultra-Ethernet, RoCE), and containers (Docker).
• Experience with distributed training workloads using PyTorch (DDP, FSDP), NeMo, or JAX; understanding AI/ML workflows from data processing to inference.
• Proficiency in at least one scripting language (e.g., Bash, Python).

Skills

• Linux system administration
• HPC infrastructure management
• Nvidia DGX server management
• Spectrum X networking
• WEKA storage integration
• AI/ML workload optimization
• Infrastructure as Code, AI OPS automation
• PyTorch, NeMo, or JAX distributed training
• Scripting (Bash, Python)
• Container technologies (Docker)
• Slurm, Kubernetes, LSF

Education

• Bachelor‚Äôs degree in computer science, Information Technology, or related technical field.

Additional Requirements

• Hybrid role located in Indianapolis, IN (relocation required)
• <5% travel