QA Engineer (Hardware)

Location: On-site at ODM factories in Taiwan. Occasional international travel to Amsterdam headquarters and datacenters in Europe and the US may be required.

Company

Nebius builds a full-stack AI cloud platform for data processing, model training, and production deployment, with infrastructure spanning compute, storage, networking, and applied AI.

What you will do

• Investigate complex server and rack failures, gather logs, run diagnostics, and drive root cause analysis with factory and engineering teams.
• Support new platform bring-up sessions and provide hands-on technical assistance during ODM lab and production activities.
• Perform visual inspections, maintain product-specific QA procedures, verify inventory records, and oversee packaging and outbound shipment readiness.
• Collect and analyze burn-in and validation data, monitor failure trends, and estimate spare-part requirements for datacenter deployments.
• Gather feedback from datacenters on packaging, shipping, cabling, rack assembly, and recurring hardware issues, then coordinate improvements with logistics, ODM partners, hardware R&D, and QA.
• Assist with on-site test infrastructure, validation environments, monitoring, triage, and real-time issue escalation.

Requirements

• Must work on-site at ODM factories in Taiwan.
• 5+ years of experience in hardware QA, manufacturing supervision, or server validation.
• Strong technical background in hardware or systems engineering, with the ability to troubleshoot complex server systems independently.
• Solid understanding of server and rack components, layouts, cabling, power, cooling, and diagnostics.
• Ability to interpret datasheets, system specifications, debug manuals, and other technical documentation.
• Knowledge of electrical engineering fundamentals, including power specifications, grounding, and signal integrity.

Nice to have

• Strong R&D background.

Culture & Benefits

• Competitive compensation and career growth opportunities.
• Learning opportunities, flexibility, and ownership.
• Collaborative, innovative, and international working environment.
• Opportunity to work on impactful AI infrastructure projects.
• Fast-paced work with meaningful impact and responsibility for shaping AI infrastructure.