Semiconductor Component Quality Engineer
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Job Location:
Cupertino, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
In this role you will engage early in semiconductor component development to ensure robustness manufacturability and reliability at scale. You will:- Lead component audits and vendor engagement to ensure compliance with Apple requirements.- Develop verified FEA models in partnership with vendors and PD FEA teams to position high-risk components in low-stress regions.- Characterize package stress limits through lab-based methods such as 3-pt bend testing warpage and stress validation.- Drive OK2Exit reviews on Apple-developed RF modules post-builds to ensure manufacturability prior to ramp.- Partner with RFHW and Operations teams to review end-to-end test coverage remove redundancy and optimize test strategy.- Manage issue resolution and continuous improvement processes including FACA Quality Alerts 8Ds and PCNs.- Apply machine learning and predictive analytics to anticipate potential component failures inform material/process selection and enable proactive system integration strategies.- Collaborate across engineering hardware and product teams to integrate predictive modeling and machine learning insights into actionable component solutions.- Stay ahead of developments in ML data analysis and materials science continually applying new methods to improve component performance and reliability.
- BS/MS/PHD in Industrial Engineering Mechanical Engineering Electrical Engineering Materials Science or related field.
- Hands-on experience in both engineering validation and data-driven predictive modeling.
- Hands-on experience in component characterization and validation including 3-point bend tests warpage analysis and other reliability methods.
- Experience auditing and ensuring component vendors conform to Apple specifications and requirements.
- Strong background in driving FACA Quality Alerts 8Ds and PCNstracking reporting and closing them in a timely manner.
- Proficiency in Finite Element Analysis (FEA) modeling and collaboration with vendors and cross-functional PD FEA teams.
- Technical expertise in machine learning and data analysis with the ability to apply advanced algorithms to component development and materials characterization.
- Experience in predictive modeling for component failures and leveraging data for proactive risk mitigation.
- Strong understanding of materials science with innovative problem-solving skills applied to component development.
- Demonstrated ability to collaborate across cross-functional hardware and operations teams integrating data-driven insights into practical solutions.
- Proven track record of data-driven decision-making and continual learning in engineering materials and machine learning domains.
Key Skills
- APQP
- Quality Assurance
- Six Sigma
- ISO 9001
- PPAP
- Minitab
- Root cause Analysis
- ISO 13485
- Quality Systems
- Quality Management
- As9100
- Manufacturing
About Company
Ask Siri to name the most successful company in the world and it might respond: Apple. And it's not just out of familial pride. Apple consistently ranks highly in profit, revenue, market capitalization, and consumer cachet. In 2018, the company became the first reach a trillion dollar ... View more
