Google

Product Engineer, ARM Servers, Storage and ML Systems

Sunnyvale, CA, USA

Sponsorship not specified$144k-$209kDetected 7 hours ago

GCPMachine LearningData AnalysisElectrical EngineeringResearch

About the role

- Bachelor's degree in Engineering or equivalent practical experience.
- 8 years of experience in electrical devices, fabrication processes, test, design for manufacturing, quality, or reliability engineering.

Lead design for manufacturing efforts across teams to ensure server/storage designs, process, test, and quality standards are enhanced for production.
Lead and guide Subject Matter Experts to ensure the product meets our specifications.
Validate product qualification plans, support product qualification testing, and review product qualification test results to ensure product performance meets requirements.
Coordinate release of New Product Introduction (NPI) Bills of Materials (BOMs) into Product Data Management (PDM) system. Perform technical review of product changes and assess impact on supply chain.

Bachelor's degree in Engineering or equivalent practical experience.
8 years of experience in electrical devices, fabrication processes, test, design for manufacturing, quality, or reliability engineering.

Master's degree in Electrical Engineering, or a related field.
10 years of experience working at a company developing supply chains, manufacturing and test for new server and storage type products for the IT industry.
Experience in data analytics and quality data systems.
Your work ensures the various pieces of Google's infrastructure fit together perfectly and keep our systems humming along smoothly for a seamless user experience.
The AI and Infrastructure team is redefining what's possible.
Work with the Product Quality Engineer to establish product quality and reliability goals.
Coordinate release of New Product Introduction (NPI) Bills of Materials (BOMs) into Product Data Management (PDM) system.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

This listing is sourced directly from Google's careers page and normalized into a canonical job model.