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Hardware Quality Engineer
Lambda
San Jose, USA
Full-time
Mid
Hybrid
Discovered 1 weeks ago
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Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers.
Our customers range from AI researchers to enterprises and hyperscalers.
Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence.
One person, one GPU.
If you'd like to build the world's best AI cloud, join us.
Note: This position requires presence in our San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.
The Operations team plays a critical role in ensuring the seamless end-to-end execution of our AI-IaaS infrastructure and hardware.
This team is responsible for sourcing all necessary infrastructure and components, overseeing day-to-day data center operations to maintain optimal performance and uptime, and driving cross company coordination through product management organization to align operational capabilities with strategic goals.
By managing the full lifecycle from procurement to deployment and operational efficiency, the Operations team ensures that our AI-driven infrastructure is reliable, scalable, and aligned with business priorities.
What You’ll Do
Track, log, and manage all quality issues arising in the data center during deployment and production environment
Perform root cause analysis (RCA) for every failure (hardware, software, process)
Analyze production system metrics and quality data to detect trends, anomalies, or weak points
Improve turnaround time (TAT) for Return Merchandise Authorization (RMA) processes
Design, monitor, and drive corrective and preventive actions (CAPA)
Implement and verify containment actions to keep systems operational until permanent fixes are applied.
Collaborate with operations, hardware, engineering, supply chain, and vendors to resolve quality issues
Capture and upload failure analysis (FA) reports and related data into Quality Management Systems (QMS)
Verify quality of spares (incoming and outgoing) to avoid repeat failures.
Define and track quality KPIs / SLAs and report on quality performance to leadership
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