Google - Austin, TX

posted 2 months ago

Full-time - Mid Level
Austin, TX
Web Search Portals, Libraries, Archives, and Other Information Services

About the position

As a GPU based Machine Learning (ML) system Supplier Quality Engineer, you will join the team responsible for setting and managing the quality and reliability standards for our semiconductor components, including custom silicon, ASICs, CPUs, and SSDs, across Google. Your role will involve improving the quality of electronic systems and semiconductor components during New Product Introduction (NPI) and maintaining it throughout their lifecycle. You will provide technical leadership, priorities, and direction for product quality and reliability while troubleshooting product or process issues. You will establish the Quality and Reliability of GPU based ML systems modules and related sub-systems and components throughout the product/IC lifecycle. This includes providing consultation to the Design, Manufacturing, and Commodity teams in the qualification and application of modules and components. You will also drive GPU diagnostic improvements with Diagnostics teams to enable faster root cause investigation. In this position, you will be responsible for driving and tracking component failures internally and leading Root Cause and Corrective Action (RCCA) with suppliers. You will work cross-functionally to define and ensure processes are in place to provide the data required to manage quality and reliability. Regular interaction with suppliers will be necessary to resolve issues and drive Return Material Authorizations, Corrective Action Requests, and Failure Analysis. This role is critical in ensuring that Google's semiconductor technology meets the highest standards of quality and reliability, ultimately contributing to the performance and success of Google's product portfolio.

Responsibilities

  • Provide technical leadership, priorities, and direction for product quality and reliability while troubleshooting product or process issues.
  • Establish the Quality and Reliability of GPU based ML systems modules and related sub-systems and components throughout the product/IC lifecycle.
  • Provide consultation to the Design, Manufacturing, and Commodity teams in qualification and application of Modules and components.
  • Drive GPU diagnostic improvements with Diagnostics teams to enable faster root cause investigation.
  • Drive and track component failures internally and lead Root Cause and Corrective Action (RCCA) with suppliers.
  • Work cross-functionally to define and ensure processes in place to provide the data required to manage quality and reliability.
  • Interface with suppliers on a regular basis to resolve issues and drive Return Material Authorizations, Corrective Action Requests, and Failure Analysis.

Requirements

  • Bachelor's degree in Electrical, Process, or Manufacturing Engineering, or equivalent practical experience.
  • 8 years of experience as a Semiconductor, Manufacturing, Quality, Reliability, Test, or Product Engineer.
  • Ability to travel as needed.

Nice-to-haves

  • Master's degree in Electrical Engineering.
  • 10 years of experience in Quality/Reliability and Semiconductor IC technology.
  • Experience in data analysis in quality reliability.

Benefits

  • Health insurance
  • Dental insurance
  • Vision insurance
  • 401(k) plan
  • Paid holidays
  • Paid time off
  • Employee stock purchase plan
  • Tuition reimbursement
  • Professional development opportunities
  • Flexible scheduling
  • Wellness programs
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service