Supplier Quality Engineer, Machine Learning Full-time

Minimum qualifications:

• 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.

Preferred qualifications:

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

About the job

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 component (e.g., custom silicon, ASICs, CPUs, SSD, etc.) technology across Google. You will improve the quality of electronic systems and semiconductor components during New Product Introduction (NPI) as well as maintain it throughout its lifecycle.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google’s product portfolio possible. We’re proud to be our engineers’ engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

The US base salary range for this full-time position is $134,000-$198,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

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 drive Root Cause and Corrective Action (RCCA) with suppliers and 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.