Google
Product Engineer, Machine Learning Accelerators
Google, Sunnyvale, California, United States, 94087
Product Engineer, Machine Learning Accelerators
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. The ML Supply Chain and Operations (MLSCO) team is responsible for the deployment of machine learning capacity in Google’s Fleet. MLSCO-NPI leads cross-functional program planning and execution to deliver next generation machine learning systems from concept to End of Life (EOL), with operational excellence and speed. Together, we are building the engine which powers Google's ML capability and driving the evolution of artificial intelligence. In the Product Engineering team, we are proud to be our engineers' engineers and love the thrill of solving complex problems to bring designs to life and make advanced technology work at massive scale. Responsibilities
Lead the technology assessment for new products. Co-work with the product team to influence design decisions, highlight manufacturing risks, and develop mitigation plans. Collaborate with Quality and Reliability Engineers to establish NPI and production goals for yield and long-term reliability. Validate product qualification plans, support reliability testing, and review results to ensure product performance meets requirements. Lead a cross-functional team towards resolution of components and build quality excursions during new product introduction build phases. Provide on-site and remote support for pre-production builds, manage the bone pile, and drive yield bridge analysis to improve product quality. Ensure factory readiness, support manufacturing line bring-up, provide product debug training and gather feedback on build issues. Minimum qualifications
Bachelor's degree in Engineering or equivalent practical experience. 5 years of experience in manufacturing. Experience in PCBA (Printed Circuit Board Assembly) and related system assembly. Experience in design for manufacturability and serviceability. Preferred qualifications
5 years of experience at a company developing supply chains in manufacturing and test. Experience working with Original Design Manufacturers (ODMs), contract manufacturers and component suppliers for data center server accelerator products (GPU, FPGA or ASIC). Experience working with contract manufacturers and suppliers to drive root cause analysis, corrective actions, and continuous process improvements. Experience with bring-up or bench testing hardware in a lab environment. Knowledge of SQL queries and scripting in Python or Bash. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
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Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. The ML Supply Chain and Operations (MLSCO) team is responsible for the deployment of machine learning capacity in Google’s Fleet. MLSCO-NPI leads cross-functional program planning and execution to deliver next generation machine learning systems from concept to End of Life (EOL), with operational excellence and speed. Together, we are building the engine which powers Google's ML capability and driving the evolution of artificial intelligence. In the Product Engineering team, we are proud to be our engineers' engineers and love the thrill of solving complex problems to bring designs to life and make advanced technology work at massive scale. Responsibilities
Lead the technology assessment for new products. Co-work with the product team to influence design decisions, highlight manufacturing risks, and develop mitigation plans. Collaborate with Quality and Reliability Engineers to establish NPI and production goals for yield and long-term reliability. Validate product qualification plans, support reliability testing, and review results to ensure product performance meets requirements. Lead a cross-functional team towards resolution of components and build quality excursions during new product introduction build phases. Provide on-site and remote support for pre-production builds, manage the bone pile, and drive yield bridge analysis to improve product quality. Ensure factory readiness, support manufacturing line bring-up, provide product debug training and gather feedback on build issues. Minimum qualifications
Bachelor's degree in Engineering or equivalent practical experience. 5 years of experience in manufacturing. Experience in PCBA (Printed Circuit Board Assembly) and related system assembly. Experience in design for manufacturability and serviceability. Preferred qualifications
5 years of experience at a company developing supply chains in manufacturing and test. Experience working with Original Design Manufacturers (ODMs), contract manufacturers and component suppliers for data center server accelerator products (GPU, FPGA or ASIC). Experience working with contract manufacturers and suppliers to drive root cause analysis, corrective actions, and continuous process improvements. Experience with bring-up or bench testing hardware in a lab environment. Knowledge of SQL queries and scripting in Python or Bash. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
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