Senior HPC Hardware Platform Lead for AI Cloud

Lambda Labs

United States

On-site

USD 150,000 - 230,000

Full time

14 days+
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Benefits offered by this job

Health insurance
Dental and vision coverage
Wellness stipend
Commuter stipend
401k Plan with company match (USA)
Flexible paid time off

Job summary

Lambda Labs is seeking a hands-on hardware NPI technical lead to own the integration of OEM and white-label HPC hardware into our cloud platform. You will drive system bring-up, documentation, vendor engagement, and production readiness for gigawatt-scale AI compute.

You will partner with HPC architects and supply chain to select configurations, triage fleet issues, and ensure on-time production while improving quality and reliability across labs and datacenters.

Qualifications

  • 5 years of technical lead experience on hardware NPI and deployment for HPC, data center, or cloud infrastructure products.
  • Hands-on experience with AI/ML hardware platforms (NVIDIA/AMD/Intel) is a plus.
  • Experience with PLM systems and BOM structure.

Responsibilities

  • Lead integration of OEM and white-label HPC hardware into Lambda’s platform.
  • Drive end-to-end hardware NPI including system bring-up, documentation, vendor engagement, and production readiness.
  • Identify, triage and resolve hardware issues across domains during NPI and fleet scale.
  • Collaborate with HPC architects to translate blueprints into concrete hardware configurations.
  • Partner with supply chain for vendor evaluation and feedback on established vendors.

Skills

Technical lead
Hardware NPI
HPC hardware
Lab bring-up
Cross-functional collaboration

Tools

PLM systems
BOM management
Vendor evaluation

Job description

Lambda Labs is seeking a hands-on hardware NPI technical lead to own the integration of OEM and white-label HPC hardware into our cloud platform. You will drive system bring-up, documentation, vendor engagement, and production readiness for gigawatt-scale AI compute.

You will partner with HPC architects and supply chain to select configurations, triage fleet issues, and ensure on-time production while improving quality and reliability across labs and datacenters.

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