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IREN

Operates renewable-powered AI GPU cloud infrastructure

Senior Product Quality Engineer - GPU / HPC

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$240k - $300k /yr

About the Job

Requirements

  • A bachelor's degree in Electrical Engineering, Mechanical Engineering, Manufacturing Engineering, or a related technical field is required.
  • At least 7 years of experience in manufacturing, test, and product quality for compute, storage, networking, or data center hardware products; experience at a hyperscaler, cloud provider, or AI infrastructure company is preferred.
  • Ability to operate with a high degree of autonomy, independently structuring quality strategy, test plans, and corrective-action recommendations, and escalating only the highest-impact or most ambiguous decisions.
  • Deep technical understanding of hardware architecture, with expertise defining requirements, testing, and validating high-performance compute and GPU systems.
  • Experience collaborating with OEM, ODM, or JDM manufacturing partners to deliver data center server and accelerator products.
  • Working expertise with manufacturing test solutions for data center infrastructure hardware, including test coverage, methodologies, and test infrastructure.
  • Hands-on experience driving manufacturing operations, including reliability and quality requirements, First Article Inspection, and defining rack acceptance criteria.
  • Knowledge of quality methodologies and tools, including Failure Analysis and Corrective Action (FACA), 8D, FMEA, SPC, and yield analysis; experience managing BOMs and engineering changes in PLM tools and defining and managing data center spares.
  • Strong hands-on problem solving, data analysis, and communication skills, with the ability to operate autonomously across design, manufacturing, quality, test, operations, and supplier teams.
  • Must be able to reliably commute to the assigned office location on scheduled in-office days under the hybrid work arrangement.
  • Pre-employment screening, including a background check and substance testing, may be required according to company policies.

Responsibilities

  • Own product and manufacturing quality strategy and processes for next-generation AI hardware systems, ensuring on-time delivery against defined quality standards.
  • Define test methods and quality standards, and drive continuous improvement projects with OEM, ODM, and JDM manufacturing partners and key commodity suppliers to meet product and process quality targets.
  • Lead cross-functional troubleshooting across rack- and system-level hardware, own the Major Issue List, and drive issues to closure.
  • Execute Failure Analysis and Corrective Action to resolve underlying technical problems and achieve quality and yield goals.
  • Engage early with Engineering teams to implement design-for-X requirements (DfM, DfA, DfT, DfQ, and DfS) and ensure products meet cycle-time, cost, quality, and yield targets.
  • Continuously evaluate and advance test coverage, methodologies, and infrastructure to maximize hardware reliability, performance, and scalability across the product lifecycle.
  • Conduct First Article Inspection and Source Inspection reviews on hardware components and assemblies.
  • Create and maintain BOMs, engineering change notifications, and manufacturing process changes through product lifecycle management tools.
  • Establish quality KPIs, including First Pass Yield, DPPM, DOA, early-life failure rate, and defect Pareto, and governance cadences with manufacturing partners and suppliers; report performance to leadership.
  • Serve as the senior technical escalation point and mentor for quality, manufacturing, and test engineers as the AI hardware portfolio scales.
  • Travel frequently to manufacturing partner, supplier, integration, and data center sites.

Desired Qualifications

  • An advanced degree is preferred.
  • Experience in manufacturing, test, and product quality at a hyperscaler, cloud provider, or AI infrastructure company is preferred.
  • Experience working on AI hardware, including NVIDIA GB200/GB300 and VR200 rack-scale programs and liquid-cooled systems, is preferred.

About the Company

IREN

Operates renewable-powered AI GPU cloud infrastructure

IREN runs renewable-powered AI cloud and digital infrastructure by operating data centers and GPU clusters. Customers access high-performance NVIDIA GPUs and AI training/inference infrastructure through cloud-based services powered by grid-connected and renewable energy assets. It differentiates itself through full vertical integration of energy assets with compute infrastructure and a focus on North America. The company aims to provide scalable, renewable-powered AI compute for enterprises and developers to support large-scale AI workloads.

Company size
501-1,000
Company stage
IPO
Headquarters
Sydney NSW, Australia
Founded
2018

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