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TensorWave

Scalable AI cloud computing for PyTorch

Operations Engineer

IT OperationsConfirmed live in the last 24 hours
Full-timeLas Vegas, NV, USA

About the Job

Requirements

  • The role requires 1–3 years of experience in a network operations center, operations center, technical support, systems administration, or a similar infrastructure operations role.
  • Experience monitoring production infrastructure using observability tools such as Grafana, Datadog, or Prometheus is required.
  • Foundational Linux systems administration skills are required, including navigating systems, reading logs, and executing diagnostic commands.
  • A basic understanding of networking fundamentals, including TCP/IP, DNS, and VLANs, is required.
  • Experience following operational runbooks and structured triage procedures in a production environment is required.
  • Strong written communication skills are required, particularly the ability to write clear incident updates and escalation summaries under time pressure.
  • The candidate must be able to stay calm, prioritize effectively, and work methodically during high-pressure situations.
  • Familiarity with ticketing and incident tracking systems such as PagerDuty, Jira, or ServiceNow is required.
  • The candidate must be willing to work shifts including nights, weekends, and holidays as part of a 24/7 coverage model.
  • The candidate must be comfortable working a rotating 12-hour shift schedule (8AM–8PM or 8PM–8AM), alternating between 3-day and 4-day work weeks on a repeating cycle, and with either day or night shifts as part of the standard rotation.
  • Offers of employment are contingent upon verification of identity and authorization to work in the United States.

Responsibilities

  • Monitor customer environments in real time across TensorWave data centers using monitoring and observability platforms.
  • Track key health indicators including GPU utilization, node availability, network performance, storage health, and Kubernetes cluster status.
  • Identify anomalies, degradations, and emerging issues before they escalate into customer-impacting events.
  • Maintain situational awareness of active customer workloads, scheduled maintenance windows, and known issues across the fleet.
  • Provide regular health summaries and flag trends that may indicate systemic risks to customer environments.
  • Serve as the first responder to customer-reported issues and system-generated alerts by performing initial triage and classification.
  • Execute established runbooks to diagnose and resolve common infrastructure issues, including node failures, connectivity problems, and resource contention.
  • Escalate issues to L2 engineering or on-site data center teams with clear, actionable context.
  • Maintain accurate incident records, including timelines, actions taken, and resolution details, in the ticketing system.
  • Communicate status updates to internal stakeholders during active incidents, ensuring visibility across operations and customer-facing teams.
  • Follow and contribute to operational runbooks and standard operating procedures, identifying gaps or improvements based on real-world incidents.
  • Assist with monitoring and alerting tuning by providing feedback on alert quality, false positive rates, and coverage gaps.
  • Document tribal knowledge, recurring issue patterns, and lessons learned to strengthen the team’s operational knowledge base.
  • Participate in post-incident reviews, contributing observations from the frontline monitoring and response perspective.
  • Support change management processes by monitoring customer environments during planned maintenance and infrastructure changes.
  • Coordinate with on-site data center operations teams for hands-on remediation activities that require physical access.

Desired Qualifications

  • Experience in a customer-facing operations role at a cloud provider, managed services provider, or colocation facility is preferred.
  • Exposure to GPU infrastructure, high-performance computing clusters, or AI/machine-learning compute environments is preferred.
  • Familiarity with Kubernetes concepts and basic container troubleshooting is preferred.
  • Scripting ability in Python, Bash, or similar for basic automation and log analysis is preferred.
  • Experience with high-performance networking concepts such as RDMA, InfiniBand, or RoCE is preferred.
  • A background working across multiple geographically distributed data center sites is preferred.
  • Relevant certifications such as CompTIA Server+, Linux+, RHCSA, or CCNA, or equivalent, are 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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