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Lambda

Cloud-based GPU services for AI training

Network Analyst

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

About the Job

Requirements

  • Foundational networking knowledge from work, study, labs, or personal projects, including how fiber and optics connect equipment.
  • Examples of following a technical task through completion and checking that the result matches the request.
  • Comfort organizing information in ticketing tools, spreadsheets, or similar systems.
  • Clear written communication and the judgment to ask for help before acting on an unclear request.
  • Interest in learning physical network infrastructure and taking on more technical responsibility over time.

Responsibilities

  • Submit approved cross-connect orders after confirming circuit identifiers and endpoints with Network Engineering.
  • Track carrier and facility requests through completion, follow up on installation dates, and flag delays or mismatched details.
  • Arrange approved disconnections after confirming the service and timing with its owner, and collect completion records.
  • Log new requests in Jira, route them to the right owner, and coordinate approved access to carrier and data center portals.
  • Help engineers prepare turn-up documents, gather test results, and check service details before activation.
  • Support circuit turn-up and testing under a senior engineer’s direction, learning how to investigate discrepancies and document findings.
  • Learn the team’s tools and contribute scripts or workflow improvements that reduce repeat manual work.
  • Maintain circuit records, supplier contacts, and project updates so engineers and delivery managers can find the information they need.
  • Organize order confirmations, test evidence, and support details for handover to Operations.
  • Share completed service changes with Supply Chain for purchasing and billing updates, and raise discrepancies with the delivery manager.

Desired Qualifications

  • Networking coursework or a certification such as Cisco Certified Network Associate (CCNA).
  • Exposure to data center work, carrier provisioning, technical support, or network inventory tools such as NetBox.
  • Some Python or other scripting experience, including coursework or personal projects.

About the Company

Lambda

Cloud-based GPU services for AI training

Lambda Labs provides cloud-based GPU services for AI training and inference via its AI Developer Cloud, powered by NVIDIA GH200 Grace Hopper hardware to efficiently train large language models and generative AI. Customers access on-demand or reserved GPUs and are billed by the hour (for example, NVIDIA H100 at about $1.99/hour); it also offers Lambda Echelon, where clients own infrastructure but pay a monthly hosting and support fee, and Lambda Stack, a software suite that helps ML teams install and upgrade tools like PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA drivers. The company differentiates itself through competitive pricing, available high-end hardware, and an integrated ML software stack that streamlines workflows. Its goal is to enable scalable, affordable AI development and deployment by providing flexible GPU access, reliable hosting, and easy software deployment for teams working with large models.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$9.1B
Headquarters
San Jose, CA
Founded
2012

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