Product Engineer, Machine Learning Accelerators
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Product Engineer, Machine Learning Accelerators
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- 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.
- 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.
- 5 years of experience at a company developing supply chains in manufacturing and test.
- Experience working with 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.
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 & 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 EOL, with operational excellence and 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're proud to be our engineers' engineers and love the thrill of solving complex problems to bring cutting-edge designs to life and make advanced technology work at 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 $115,000-$166,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 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.
Seniority level
Seniority level
Not Applicable
Employment type
Employment type
Full-time
Job function
Job function
Other, Information Technology, and EngineeringIndustries
Information Services and Technology, Information and Internet
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