Senior Product Engineer, ML Accelerators
About The Position
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 Machine Learning Supply Chain and Operations (MLSCO) team is responsible for the deployment of Machine Learning capacity in Google’s Fleet. MLSCO New Product Introduction (NPI) leads cross-functional program planning and execution to deliver next generation Machine Learning systems from Concept to End of Life (EOL). Together, we are building the engine which powers Google's Machine Learning capability and driving the evolution of artificial intelligence. 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.
Requirements
- Bachelor's degree in Electrical Engineering, a related field, or equivalent practical experience.
- 8 years of experience as a Manufacturing, Quality, Reliability, or Product Engineer.
- 5 years of experience with a company developing supply chains in manufacturing and testing.
- Experience working with Original Device Manufacturers (ODMs), contract manufacturers and component suppliers for data center class products.
Nice To Haves
- Master's degree in Electrical Engineering, or a related field.
- 10 years of experience developing supply chains in manufacturing and testing.
- 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.
Responsibilities
- Lead reviews between Design and Operations Engineering to drive deliverables that are key to implementing the manufacturing plan, such as Design for Excellence (DFx) and test strategy.
- 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. Drive yield bridge analysis to improve product quality.
- 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. Validate product qualification plans, support reliability testing and ensure product performance meets requirements.
- Lead cross-functional team towards resolution of component/build quality excursions during NPI build phases.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
