<div>Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.</div><div> </div>

Nava

About Nava&nbsp;&nbsp;
Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.&nbsp;&nbsp;
About the Role&nbsp;
The Network Deployment team builds and validates the high-speed switching and GPU networking that connects Nava's production AI clusters. This is a hands-on engineering role.&nbsp;
Deploy and validate high-speed GPU cluster networks, including InfiniBand, RoCE, and Ethernet fabrics. Configure switches, automate provisioning, troubleshoot connectivity, benchmark network performance, and ensure production-ready infrastructure.&nbsp;
What You’ll Do&nbsp;
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Configure InfiniBand/RoCE, Ethernet leaf-spine, storage and management networking.&nbsp;
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Perform optics, cable, routing, topology and link-state validation.&nbsp;
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Test RDMA reachability, bandwidth, latency and fabric congestion under load.&nbsp;
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Automate switch provisioning, preflight tests and configuration checks.&nbsp;
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Investigate hardware, routing and network fabric issues with compute/storage teams.&nbsp;
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Produce acceptance evidence, as-built documentation and operational handover.&nbsp;
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Configure and tune PFC/ECN for lossless RoCEv2 (or InfiniBand credit flow), validate rail-optimized topology and adaptive routing, and run NCCL bus-bandwidth acceptance tests.&nbsp;
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Use UFM (InfiniBand) and NetQ / Spectrum-X telemetry to verify PFC-pause is near zero and GPUDirect RDMA / BlueField DPU paths perform at line rate.&nbsp;
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What You’ll Need&nbsp;
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5–8 years in hands-on data center networking.&nbsp;
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Strong BGP, L2/L3, EVPN/VXLAN and high-speed switching knowledge.&nbsp;
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Linux debugging and Python/Ansible automation.&nbsp;
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Experience with Arista, Cisco, NVIDIA Networking or similar platforms.&nbsp;
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Within that, hands-on GPU / AI-datacenter exposure is what we weigh most — we value demonstrated depth over years, as the field is still emerging.&nbsp;
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<li>RDMA/RoCEv2, InfiniBand, PFC/ECN and GPU cluster testing.&nbsp;</li>
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