Data Center Quality Engineer, Machine Learning GPU Platforms

2 Weeks ago • 8 Years + • Manufacturing

Job Summary

Job Description

As a Data Center Quality Engineer at Google, you'll be responsible for managing multiple complex projects, leading cross-functional teams, and implementing process improvements. You'll leverage your expertise in data analysis, statistical methodologies (DOE, SPC, Six Sigma, etc.), and quality engineering to ensure the reliability and performance of Google's custom-designed machine learning GPU platforms. Responsibilities include root cause analysis, driving resolution of technical issues, developing innovative solutions, gathering and analyzing data, presenting performance metrics, and creating/improving technical documentation. The role requires strong technical leadership, project management skills, and up to 20% travel.
Must have:
  • Bachelor's degree in relevant field
  • 8+ years experience in quality/manufacturing
  • Data analysis & visualization skills (SQL, Python etc.)
  • Statistical methodologies (DOE, SPC, Six Sigma)
  • Technical leadership & problem-solving
Good to have:
  • Master's degree
  • Cross-functional team leadership
  • Project management experience
  • Executive communication skills

Job Details


Minimum qualifications:

  • Bachelor's degree in Electrical, Computer Science, Computer Engineering, Mechanical, Industrial, Materials or equivalent practical experience.
  • 8 years of experience in quality or manufacturing or product engineering of cloud hardware technology or electronic hardware systems.
  • Experience in data analysis and visualization using SQL, JMP, R, Matlab, Tableau, PowerBI, or Python.
  • Experience with advanced statistical (or statistics based) methodologies e.g., design of experiments (DOE), statistical process controls (SPC), six sigma, FMEA, ANOVA, MSA, Fishbone or similar methodologies.

Preferred qualifications:

  • Master's degree in Electrical, Computer Science, Computer Engineering, Mechanical, Industrial, Materials or equivalent practical experience.
  • Experience leading cross-functional engineering teams using a practical and solution-oriented approach.
  • Experience of technical leadership, project management, and executive communication.

About the job

Google's custom-designed equipment makes up one of the largest and most powerful computing infrastructures in the world. The Manufacturing Operations team is responsible for providing the manufacturing capability to deliver this state-of-the-art physical infrastructure. As a Manufacturing Engineer, you evaluate the product designs and create the processes, tools and procedures behind Google’s powerful search technology. When vendors build parts for our infrastructure, you’re right there alongside ensuring manufacturing processes are repeatable and controlled. You collaborate with Commodity Managers and Design Engineers to determine Google’s infrastructure needs and product specifications. 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.

As a Quality Engineer on this team you will manage multiple projects, some of which will be complex and large-sized, lead cross-team initiatives, and identify/implement process improvements for the larger organization. You will be required to travel up to 20% of the time.

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.

Responsibilities

  • Provide technical leadership, set priorities, complete root cause analysis, and drive resolution of technical issues for product quality and predictable field deployment.
  • Initiate, drive, and implement innovative product, process, tools development/improvement projects in a cross-functional environment.
  • Gather and analyze manufacturing/field data within the data center environment to extract insights and continuous improvement opportunities.
  • Monitor, review, and present product performance data and metrics to stakeholders in a way that enables data-driven decision making.
  • Review, edit, improve, and create technical documentation (e.g., deployment guides, population documents, repairs guides) based on data, investigations, technician feedback, and quality fundamentals.

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