Senior Product Engineer, ML Accelerators
Please submit your resume in English - we can only consider applications submitted in this language.
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
Note: Google's hybrid workplace includes remote roles.Remote location: Mexico.
Minimum qualifications:
- Bachelor's degree in Engineering or equivalent practical experience.
- 8 years of experience in manufacturing.
- Experience in design for manufacture and serviceability.
- Experience in printed circuit board assembly (PCBA) and related system assembly.
Preferred qualifications:
- Master's degree or PhD in Electrical, Mechanical, Industrial, Materials, or a related engineering field.
- 10 years of experience in developing supply chains in manufacturing and testing.
- Experience with contract manufacturers and suppliers to drive root cause analysis, corrective actions, and continuous process improvements.
- Experience working with ODMs, and component suppliers for data center server accelerator products (e.g., GPU, FPGA, or ASIC).
- Experience in 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-New Product Introduction (NPI) leads cross-functional program planning and execution to deliver next-generation machine learning systems from concept to end of life with operational speed.
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.
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 reliability. Validate product qualification plans, support reliability testing, and review results to ensure product performance meets requirements.
- Lead cross-functional team towards resolution of components and build quality excursions during NPI 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 and drive yield bridge analysis to improve product quality.
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