Minimum qualifications:
- Bachelor's degree in Engineering or equivalent practical experience.
- 8 years of experience in manufacturing.
- Experience in Printed Circuit Board Assembly (PCBA) and related system assembly.
- Experience in design for manufacturability and serviceability.
Preferred qualifications:
- Master's degree or PhD in Electrical, Mechanical, Industrial, Materials, or a related engineering field.
- 10 years of experience at a company developing supply chains in manufacturing and testing.
- Experience working with Original Device Manufacturers (ODMs), contract manufacturers and component suppliers for data center server accelerator products (e.g., GPU, FPGA or ASIC).
- Experience working with contract manufacturers and suppliers to drive root cause analysis, corrective actions and continuous process improvements.
- Experience of bring-up or bench testing hardware in a lab environment.
- Knowledge of SQL queries and scripting in Python or Bash.
About the job
The Machine Learning 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 Machine Learning capability and driving the evolution of artificial intelligence. In the Product Engineering team, we're proud to be our engineers' and solve complex problems to bring designs to life and make advanced technology work at a massive scale.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $144000 - $209000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
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 New Product Introduction (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 cross-functional teams towards resolution of components and build quality excursions during New Product Introduction build phases.
- Provide on-site and remote support for pre-production builds. Ensure factory readiness, support manufacturing line bring-up, provide product debug training and gather feedback on build issues. Manage the bonepile and drive yield bridge analysis to improve product quality.
