AI Operations & Infrastructure Engineer

Title: AI Operations & Infrastructure Engineer

Location: Fort Meade, MD

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 Infini Band 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, Blue Field DPUs, cables, and transceivers
• Perform firmware upgrades, hardware validation, and storage setup
• Configure and administer physical and logical resources, including MIG partitioning and Blue Field platforms
• Install and configure operating systems, cluster software, drivers, containers (Docker), and NGC CLI
• Manage and orchestrate clusters using NVIDIA Base Command Manager, Slurm, Pyxis, Enroot, and Run:
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• Perform stress, benchmarking, and burn-in tests using HPL, NCCL, NVIDIA Nemo, and Cluster Kit
• Verify cabling, firmware/software versions, and network signal quality
• Troubleshoot and resolve hardware, software, storage, and performance faults
• Replace faulty components and optimize systems for AMD/Intel platforms
• Monitor, document, and report on cluster health, resource usage, and job performance
• Ensure secure, efficient, and scalable operation of NVIDIA AI infrastructure, including user access and workload management

• Qualified candidates must hold an active NVIDIA Professional Certification in either AI Networking, AI Infrastructure, or AI Operations
• Prior direct, hands-on professional experience administering NVIDIA GPU and data processing unit (DPU) technologies, AI software stacks, and data center environments for high-performance AI workloads
• Comprehensive expertise in deploying and maintaining AI compute platforms, requiring proficiency in containerization and workload orchestration using Docker, Kubernetes, Slurm, NVIDIA Base Command Manager, and Run:
  
  Ai
• Must be capable of configuring physical and logical resources, including Multi-Instance GPU (MIG) partitioning and Blue Field platforms, while overseeing critical facility elements such as power, cooling, and storage solutions
• The ability to demonstrate advanced skills in AI networking, specifically configuring and optimizing high-performance Infini Band and Ethernet fabrics to ensure maximum throughput and minimal latency
• Current active TS/SCI clearance with a CI Polygraph

Equal Opportunity Employer/Veterans/Disabled