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TensorWave

Scalable AI cloud computing for PyTorch

Senior Network Engineer - Operations

Network Engineering & AdministrationConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • At least 5 years of data center network operations experience.
  • Experience with multiple vendors and network operating systems, including Juniper, Cisco, Arista, Whitebox, Junos, IOS/IOS-XE, NX-OS, EOS, and SONiC.
  • Hands-on experience with large Ethernet fabrics and edge networks.
  • Strong understanding of scale-up versus scale-out architectures.
  • Experience operating production networks at scale.

Responsibilities

  • Operate and maintain large Ethernet fabrics.
  • Participate in an on-call rotation and incident response.
  • Execute maintenance, upgrades, and hardware replacements.
  • Troubleshoot latency, packet loss, and connectivity issues.
  • Support continuous scale-out growth of production networks.
  • Build or extend automation and tooling to streamline operations using Python, Go, Ansible, and Git-backed workflows.

Desired Qualifications

  • Experience with 100G+ environments.
  • Familiarity with optical standards and transceiver types, including 100G/400G/800G, SR/LR/ER, and DWDM.
  • Exposure to AI, GPU, or HPC environments.
  • Automation and scripting to reduce operational toil using Python, Go, and Ansible; experience with network APIs/SDKs, CI/CD for network changes, and telemetry/log parsing for rapid incident triage.

About the Company

TensorWave

Scalable AI cloud computing for PyTorch

TensorWave provides cloud-based compute power for large-scale AI workloads, with a focus on PyTorch. It runs on AMD MI300X hardware with a scalable fabric that can pool vast amounts of VRAM, and customers access this power through a subscription or pay-as-you-go model. The service allocates the requested compute and storage behind a managed fabric, charging based on usage to offer flexibility and cost-efficiency. TensorWave aims to be a leading AI cloud provider by offering large VRAM pools and strong price‑to‑performance, helping enterprises and research institutions train, fine-tune, and deploy large models without owning hardware.

Company size
51-200
Company stage
Series B
Total funding
$493M
Headquarters
Las Vegas, NV
Founded
2023

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