AI Operations & Infrastructure Engineer

Clearance: TS/SCI with a CI Polygraph

• Manage and maintain AI computing platforms, including GPUs and other specialized hardware
• Install and configure GPU drivers and software
• Oversee the AI software stack and tools
• Implement and manage containerization technologies like Docker and Kubernetes
• Configure and optimize networking infrastructure for AI workloads, including InfiniBand and Ethernet
• Manage storage solutions for AI data, considering performance and capacity requirements
• Deploy and manage data processing units (DPUs) to accelerate data center workloads
• Monitor and manage AI cluster health and resource utilization
• Implement workload management and scheduling tools like Slurm and Kubernetes
• Ensure efficient power and cooling for AI infrastructure to maintain optimal operating conditions
• Configure high-performance networking solutions for AI and machine learning workloads
• Optimize network performance to ensure maximum throughput and minimal latency for AI computations
• Implement and fine-tune network protocols to enhance data transfer speeds and efficiency
• Integrate NVIDIA networking products with existing AI infrastructure, including servers, GPUs, and storage systems
• Deploy networking solutions in data centers to ensure seamless connectivity between AI components
• Diagnose and resolve networking issues impacting AI workloads to maintain optimal system performance
• Provide technical support and guidance to teams managing AI infrastructure
• Collaborate with data scientists, researchers, and IT professionals to understand networking requirements and challenges
• Lead deployment and validation of servers and systems for AI enabled platforms
• Configure and manage network topologies, BMC, OOB, TPM, power, and cooling
• Install, upgrade, and validate GPU-based servers, BlueField DPUs, cables, and transceivers