IREN
Senior Product Quality Engineer – GPU / HPC
$240K–$300K
San Francisco, California · Hybrid · Senior · Full-time · Posted Oct 23, 2026
- Experience
- 7+ years.
- Education
- Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Manufacturing Engineering, or a related technical field; advanced degree preferred.
- Visa sponsorship
- Participates in E-Verify and provides the federal government with Form I-9 information to confirm authorization to work in the United States.
About the job
Owns quality strategy, testing, and failure analysis for rack-scale AI and accelerated-computing hardware from new product introduction through volume production and sustaining.
What you'll do
- Set quality standards and test methods; drive quality and yield improvements with manufacturing partners and suppliers.
- Lead rack- and system-level troubleshooting, failure analysis, and corrective actions; track major issues to closure.
- Manage lifecycle quality activities, including design-for-X requirements, inspections, quality KPIs, and BOM and engineering changes.
What they ask for
- Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Manufacturing Engineering, or a related technical field.
- 7+ years of experience in manufacturing, test, and product quality for compute, storage, networking, or data center hardware.
- Deep understanding of hardware architecture and demonstrated expertise defining requirements, testing, and validating high-performance compute and GPU systems.
- Experience with OEM/ODM/JDM manufacturing partners, manufacturing test solutions, First Article Inspection, quality methodologies, and PLM tools.
Nice to have
- Advanced degree.
- Experience with AI hardware, including NVIDIA GB200/GB300 and VR200 rack-scale programs and liquid-cooled systems.
Pay
USD $240,000-$300,000/annum (base salary)
Tools
GPU, FACA, 8D, FMEA, SPC, PLM, NVIDIA GB200/GB300, VR200
AI focus
Ensures the quality, reliability, testing, and manufacturing readiness of rack-scale AI hardware used for AI training and inference.
Model-written summary · the original posting is authoritative