Hardware Quality Engineer – AI Infra (Equity & Bonus)

Google; Austin (TX); On-site; USD 159,000 - 230,000; Full time

Job summary

Google is seeking a Customer Quality Engineer (Hardware Engineer) to work closely with customers and internal teams to improve hardware quality across Google Cloud hardware solutions. The role involves understanding customer impacts, driving cross-functional investigations, and leading initiatives to maximize reliability and product quality.

This position emphasizes collaboration with engineering and product teams, with an emphasis on AI/ML computing hardware, including accelerators, and a focus

Qualifications

• Bachelor's degree or equivalent practical experience.
• 4 years of manufacturing or validation experience with CPU, dGPU, or TPU.
• 3 years of experience with quality and reliability of technical infrastructure.
• Experience with semiconductor and production manufacturing flows, and implementing test screens, ATE and DFT tests, and transistor parametrics.
• Experience troubleshooting and advocating for customer needs.
• Experience with System Architecture (CPU, TPU, I/O interfaces, or memory).

Responsibilities

• Track and manage customer hardware observations and guide priorities.
• Collaborate with internal engineering to diagnose and gauge impact and tool development.
• Work with Product, Quality, and Engineering teams to drive improvements and coordinate with SRE.
• Assess reliability and quality implications of hardware/software changes on deployed hardware.
• Engage directly with customers to understand hardware quality and plan future improvements.

Skills

Manufacturing experience

Customer advocacy

System architecture

Troubleshooting

Hardware quality

IT infrastructure reliability

Education

Bachelor's degree in CS/IS or related field

Job description

Google is seeking a Customer Quality Engineer (Hardware Engineer) to work closely with customers and internal teams to improve hardware quality across Google Cloud hardware solutions. The role involves understanding customer impacts, driving cross-functional investigations, and leading initiatives to maximize reliability and product quality.

This position emphasizes collaboration with engineering and product teams, with an emphasis on AI/ML computing hardware, including accelerators, and a focus