Product Engineer, Machine Learning and GPU Accelerators
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Minimum qualifications:
- Bachelor's degree in Engineering or equivalent practical experience.
- 8 years of experience in manufacturing.
- Experience in design for manufacturability and serviceability.
- Experience in PCBA (Printed Circuit Board Assembly) 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 at a company 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 working with Original Design Manufacturers (ODMs), contract manufacturers and component suppliers for data center server accelerator products (Graphics Processing Unit (GPU), FPGA or ASIC).
- 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 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 best speed. Together, we are building the engine which powers Google's cutting edge ML capability and driving the evolution of artificial intelligence.
In the Product Engineering team, we are proud to be our engineers' engineers and solving complex problems to bring cutting-edge designs to life and make advanced technology work at a massive scale.
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.
The US base salary range for this full-time position is $134,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or 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 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. 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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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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