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Company Overview
This company is a global leader in innovative memory and storage solutions. Through its global brands, it delivers high-performance memory and storage technologies including Dynamic Random-Access Memory (DRAM) and NAND flash memory. The company’s solutions are used in leading-edge computing, consumer, enterprise storage, data center, mobile, embedded, and automotive applications.
Principal Product Engineer (Advance Data Analytics), Heterogeneous Integration Group (HIG), High Bandwidth Memory (HBM) Product Engineering
Key Responsibilities
As a key member of cross-functional teams, this individual will take ownership of cumulative yield and lead impactful initiatives that significantly enhance overall yield and quality improvement, driving substantial benefits for the organization. They will utilize in-house statistical tools, machine learning, and AI for engineering data analysis to enhance yields and reliability, integrating these improvements within the Dispo workflow. This role involves developing state-of-the-art algorithms, including Machine Learning and Deep Learning models, to advance data mining and pattern recognition for quality enhancement, yield improvement, wafer/die level screening, and efficiency enhancement.
The Principal Product Engineer will develop, validate, and deploy product-disposition solutions (wormhole) to ensure quality and reduce Defects Per Million (DPM) through a comprehensive product disposition program/workflow. They will also create a deviation alert system to monitor yield loss, characteristic/parameter trends, and wafer/die/cube shading. Collaborating with IT, Manufacturing, and Operations teams will be essential to develop and enhance the data infrastructure pipeline using cloud technologies to support reliability and engineering assessments.
Mentorship and development of team members will be a key responsibility, fostering growth within the team and the organization. This individual will work closely with various cross-functional teams, including Fab, HBM Technology Development, HBM Design, System Development, and Quality/Reliability teams, to ensure the holistic development and successful shipping of end products. They will promote innovation and drive changes that provide a technical advantage over competitors, maintaining the company’s competitive edge in the market, and collaborate with cross-functional teams to develop, deploy, and validate AI/ML models aimed at enhancing key performance indicators (KPIs) such as Quality, Cost, Cycle Time, and Scale.
Requirements
Bachelor’s or Master’s degree in Engineering, Computer Science, Statistics, Artificial Intelligence, or related fields.
At least 10 years of experience in data analytics/science industry. Experience in Product Engineering or the semiconductor industry is preferred.
Proven experience in leading analytic projects from conception to completion.
Demonstrates strong leadership skills and technical skills with a strong understanding of data analytics, data extraction, and analysis tools, including proficiency in Python and SQL.
Dedicated and highly motivated with a flexible approach towards adapting to different roles in a dynamic working environment (from leading the team to leading technical programs).
Proven track record of collaborative work within/across teams to address sophisticated business and engineering problems.
Possesses strong communication and presentation skills to clearly convey complex data insights to stakeholders.
Strong sense of responsibility and accountability towards the assigned role with a professional work ethic.
Proficient in scripting, coding, Google Cloud Platform, and statistical analysis tools such as JMP, Tableau, Power BI will be an advantage.
Willingness to work on-site in Singapore with international travel to Taiwan.
Disclaimer
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