Vultr - GPU Fabric Engineer
Requirements
• 3–7 years of experience in network engineering, HPC fabric, or GPU infrastructure • Hands-on experience with InfiniBand and/or RoCE fabrics in GPU cluster environments • Experience with NVIDIA UFM for fabric management, monitoring, and diagnostics • Strong understanding of RDMA transport, lossless Ethernet design, and congestion management (PFC, ECN, DCQCN) • Experience with GPU cluster networking and distributed communication libraries (NCCL, MPI) • Familiarity with GPU platforms and their interconnect requirements (NVIDIA NVLink, NVSwitch, ConnectX) • Experience with fabric diagnostic tools (ibstat, ibqueryerrors, perfquery, etc.) • Proficiency in Python or Bash for scripting and validation • Basic understanding of Linux systems and server hardware • Strong troubleshooting and analytical skills across network and system layers
Responsibilities
• Validate and troubleshoot InfiniBand and RoCE fabrics during GPU cluster bring-up and expansion • Tune fabric performance parameters for distributed AI workloads (NCCL, MPI, collective operations) • Monitor and manage fabrics using NVIDIA UFM (Unified Fabric Manager) for health, topology, and performance visibility • Diagnose and resolve fabric-level issues including link errors, congestion, packet loss, and path asymmetry • Optimize RDMA transport settings, PFC/ECN behavior, and lossless queue configuration for GPU traffic • Validate fabric performance benchmarks and ensure line-rate throughput for AI workloads • Collaborate with GPU Engineers to correlate fabric health with workload performance • Collaborate with networking teams on fabric provisioning, configuration, and remediation • Respond to fabric alerts and degradation events across production GPU clusters • Document fabric troubleshooting procedures, tuning parameters, and validation runbooks
Benefits
• $125,000 - $135,000 • Final compensation will vary depending on years of experience, background/skill set, location, and applicable laws. • INCLUSION & PRIVACY
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