<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 Compute &amp; Storage SRE &amp; Operations team leads reliability engineering for production NVIDIA GPU fleets and distributed storage, ensuring customer workloads see healthy capacity, resilient storage and rapid recovery from infrastructure faults.&nbsp;
Own reliability and performance of production GPU compute and storage infrastructure. Lead hardware fault management, GPU health monitoring, incident recovery, lifecycle management, automated remediation, and infrastructure availability improvements.&nbsp;
What You’ll Do&nbsp;
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Own GPU availability, node health, storage SLIs, capacity and service recovery objectives.&nbsp;
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Lead diagnosis of GPU Xid/ECC, PCIe, NVLink, firmware, OS and hardware faults.&nbsp;
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Own storage availability and performance investigations, recovery tests and lifecycle processes.&nbsp;
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Implement automated node isolation, hardware triage, repair/replace workflows and return-to-service checks.&nbsp;
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Improve observability using DCGM, Linux telemetry, service monitoring and fleet health dashboards.&nbsp;
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Lead cross-functional incidents and reliability improvements with OEMs, networking and platform engineering.&nbsp;
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What You’ll Need&nbsp;
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10–15 years in Linux production infrastructure, SRE, HPC or distributed systems with people leadership.&nbsp;
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Hands-on GPU/server diagnostics, Linux internals and hardware lifecycle management.&nbsp;
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Operational knowledge of distributed or parallel storage such as WEKA, Lustre, BeeGFS, IBM Storage Scale or Ceph.&nbsp;
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Python/Go automation, incident management and observability systems.&nbsp;
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Familiarity with Kubernetes, Slurm and fleet-wide infrastructure operations.&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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Experience operating large NVIDIA GPU clusters and NVLink/NVSwitch environments.&nbsp;
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Hyperscaler or high-availability compute operations environments.&nbsp;
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