InfiniBand Engineer (High-Performance Networking)
Job Description
Job Summary
We are seeking a highly skilled InfiniBand Engineer with strong expertise in advanced networking technologies to design, deploy, and support high-performance, low-latency network infrastructures. The ideal candidate will have hands-on experience with InfiniBand fabrics, data center networking, and large-scale distributed computing environments (HPC / AI / ML clusters).
Key Responsibilities
Design, implement, and manage large-scale InfiniBand (IB) fabrics in data center and HPC environments. Configure and troubleshoot InfiniBand switches and adapters (e.g., Mellanox / NVIDIA IB platforms). Perform fabric bring-up, subnet management (OpenSM), partitioning, and performance tuning. Monitor and optimize network performance, latency, throughput, and congestion control. Integrate InfiniBand with Ethernet-based networking environments. Support RDMA technologies (RoCE, iWARP) and GPUDirect environments. Collaborate with system, storage, and compute teams to support AI/ML and distributed workloads. Perform firmware upgrades, patching, and capacity planning. Troubleshoot Layer 2 / Layer 3 networking issues (BGP, OSPF, VLAN, VXLAN, etc.). Maintain documentation, network diagrams, and SOPs.
Required Skills & Qualifications
5+ years of networking experience with strong fundamentals (TCP/IP, routing, switching). Hands-on experience with InfiniBand technologies (HDR/NDR preferred). Experience with NVIDIA / Mellanox Technologies switches and adapters. Strong understanding of RDMA, congestion control, QoS, and low-latency tuning. Experience with subnet managers (OpenSM) and fabric diagnostic tools. Solid understanding of BGP, OSPF, EVPN-VXLAN, MPLS (good to have). Experience in HPC, AI/ML cluster networking environments is highly preferred. Familiarity with Linux networking and troubleshooting tools. Experience with automation (Python, Ansible) is a plus.
Preferred Qualifications
Experience supporting large GPU clusters. Knowledge of storage networking (NVMe-oF, parallel file systems). Experience with monitoring tools and telemetry systems. Networking certifications (CCNP/CCIE or equivalent).
Key Competencies
Strong analytical and troubleshooting skills Ability to work in high-performance, mission-critical environments Excellent documentation and communication skills Proactive problem-solving mindset
We are seeking a highly skilled InfiniBand Engineer with strong expertise in advanced networking technologies to design, deploy, and support high-performance, low-latency network infrastructures. The ideal candidate will have hands-on experience with InfiniBand fabrics, data center networking, and large-scale distributed computing environments (HPC / AI / ML clusters).
Key Responsibilities
Design, implement, and manage large-scale InfiniBand (IB) fabrics in data center and HPC environments. Configure and troubleshoot InfiniBand switches and adapters (e.g., Mellanox / NVIDIA IB platforms). Perform fabric bring-up, subnet management (OpenSM), partitioning, and performance tuning. Monitor and optimize network performance, latency, throughput, and congestion control. Integrate InfiniBand with Ethernet-based networking environments. Support RDMA technologies (RoCE, iWARP) and GPUDirect environments. Collaborate with system, storage, and compute teams to support AI/ML and distributed workloads. Perform firmware upgrades, patching, and capacity planning. Troubleshoot Layer 2 / Layer 3 networking issues (BGP, OSPF, VLAN, VXLAN, etc.). Maintain documentation, network diagrams, and SOPs.
Required Skills & Qualifications
5+ years of networking experience with strong fundamentals (TCP/IP, routing, switching). Hands-on experience with InfiniBand technologies (HDR/NDR preferred). Experience with NVIDIA / Mellanox Technologies switches and adapters. Strong understanding of RDMA, congestion control, QoS, and low-latency tuning. Experience with subnet managers (OpenSM) and fabric diagnostic tools. Solid understanding of BGP, OSPF, EVPN-VXLAN, MPLS (good to have). Experience in HPC, AI/ML cluster networking environments is highly preferred. Familiarity with Linux networking and troubleshooting tools. Experience with automation (Python, Ansible) is a plus.
Preferred Qualifications
Experience supporting large GPU clusters. Knowledge of storage networking (NVMe-oF, parallel file systems). Experience with monitoring tools and telemetry systems. Networking certifications (CCNP/CCIE or equivalent).
Key Competencies
Strong analytical and troubleshooting skills Ability to work in high-performance, mission-critical environments Excellent documentation and communication skills Proactive problem-solving mindset
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