2.1
2.1 AI Cluster Engineering & GPU Fleet Operations
10K+ GPU supercomputing clusters, rack-scale topologies, rail-optimized networks, DCGM telemetry, MIG partitioning, and automated fleet self-healing.
10K+ GPU SuperPOD Clusters & Topologies
Rack-scale GPU systems, non-blocking fat-tree fabrics, rail-optimized network design, fault-domain isolation, and 10K+ GPU scaling efficiency optimization.
🏢 Companies
CoreWeave、AWS、Microsoft Azure、Google Cloud、Oracle Cloud、Lambda Labs、Crusoe、Nebius
🛠️ Tech Stack
GPU ClusterSuperPODFat-TreeRail-OptimizedFault DomainsScaling EfficiencyBespoke AI Cloud
💼 Roles & Salary
GPU Infrastructure Engineer、HPC Engineer、Cluster Engineer
💰 $220K - $460K / year (AI Cloud Infra) | ¥600K - ¥1.5M / year
📚 Prerequisites: Distributed HPC Architecture • Linux Kernel & NUMA Tuning • GPU Topology & Bus Bandwidth • Hardware Fault Tolerance
GPU Fleet Operations & Node Health Automation
NVIDIA DCGM continuous telemetry, Multi-Instance GPU (MIG) slicing, bare-metal provisioning, firmware lifecycle automation, and self-healing node drain pipelines.
🏢 Companies
NVIDIA、CoreWeave、AWS、Google Cloud、Microsoft Azure
🛠️ Tech Stack
DCGMMIG SlicingFleet ReliabilityBare-metal ProvisioningFirmware LifecycleNode RemediationSLO Monitoring
💼 Roles & Salary
GPU Infrastructure Engineer、Fleet Reliability Engineer、DevOps / SRE
💰 $195K - $420K / year (Fleet Reliability) | ¥500K - ¥1.3M / year
📚 Prerequisites: DCGM Drivers & Profiling Counters • IPMI & Redfish Bare-metal Specs • Prometheus / Grafana Telemetry • Python / Go Cluster Automation