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Product Quality Engineer
| Company | Google |
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| Location | Austin, TX, USA |
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| Salary | $138000 – $202000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s |
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| Experience Level | Senior |
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Requirements
- Bachelor’s degree in Mechanical Engineering, Industrial Engineering, Materials Engineering, or related engineering discipline, or equivalent practical experience.
- 5 years of experience working in computing hardware quality, product engineering, or electronic hardware systems issue resolution.
- Experience in data analysis and visualization using SQL, JMP, or Python.
- Experience working with reliability and quality test data or manufacturing execution systems.
Responsibilities
- Develop and execute the overall product quality strategy and assurance plans for next-generation AI hardware systems, collaborating with stakeholders.
- Own the overall product quality process, spanning internal and external development through successful deployment and production at scale, ensuring consistent quality across all stages.
- Develop predictive failure models using advanced statistical methods. Track key quality metrics and extract actionable insights using advanced analytics and statistical methods.
- Lead the resolution of product issues during manufacturing and field operations using structured problem solving techniques such as eight disciplines (8D).
- Communicate with cross-functional teams and management, distilling technical information into clear, concise presentations to facilitate informed decision-making and drive alignment on quality initiatives. Provide regular updates and reports on quality metrics and improvement initiatives.
Preferred Qualifications
- Master’s degree or PhD in Electrical, Mechanical, Industrial, Materials, or a relevant engineering discipline.
- Certified Reliability/Quality Engineer (CRE/CQE) certification or equivalent experience.
- 7 years of experience in Hardware Quality, Reliability, Product Engineering, Test Engineering or Manufacturing of cloud hardware systems.
- Experience leading cross-functional engineering teams using a practical and solution-oriented approach.
- Experience with advanced statistical or statistics based methodologies (e.g., design of experiments, statistical process controls, six sigma, etc.).
- Experience in technical leadership, project management, and executive communication.
Benefits
No information provided on Benefits.
