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TensorWave

Scalable AI cloud computing for PyTorch

Electrical Engineer - Data Center

Power Systems EngineeringConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A Bachelor of Science degree in Electrical Engineering is required.
  • At least 7 years of experience in the design, construction, and commissioning of mission-critical electrical systems is required.
  • Expert-level knowledge of high-voltage and low-voltage power distribution systems is required.

Responsibilities

  • Perform detailed design review and technical validation of high-power electrical distribution systems, including medium-voltage switchgear, uninterruptible power supplies, paralleling switchgear, and generator plants.
  • Design and model electrical infrastructure to support next-generation AI hardware, focusing on high-density power delivery at the rack level and ensuring system reliability, including fault tolerance and selectivity.
  • Conduct power quality studies, short-circuit analysis, and arc-flash analysis using industry software such as SKM and ETAP.
  • Provide subject-matter expertise during construction, commissioning (Level 4/5 testing), and operation to resolve complex electrical issues.
  • Ensure all electrical designs adhere to NFPA 70 (NEC), IEEE, and corporate safety standards.

Desired Qualifications

  • A Professional Engineer (P.E.) license is preferred.
  • Experience with battery energy storage systems (BESS) is preferred.

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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