About the role
AI summarisedThis role focuses on leveraging data analytics, machine learning, and AI to improve product quality, yield, and reliability in semiconductor manufacturing, specifically for High Bandwidth Memory (HBM) products. The engineer will develop and deploy product disposition solutions, create deviation alert systems, build advanced algorithms for pattern recognition, and collaborate across teams including Fab, design, and quality to drive innovation and technical advantage. The position requires strong technical and communication skills, with mentorship responsibilities and on-site work in Singapore involving international travel.
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Key Responsibilities
- Develop, validate and deploy product-disposition solutions (wormhole) to ensure quality and reduce Defects Per Million (DPM) through a comprehensive product disposition program/workflow
- 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
- Create a deviation alert system to monitor yield loss, characteristic/parameter trends, and wafer/die/cube shading
- Develop 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
- Actively mentor and develop team members to foster growth and development within the team and the organization
- 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
- Promote innovation and drive changes that provide a technical advantage over competitors, maintaining the company's competitive edge in the market
- 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 Electrical and Electronics Engineering, Statistics, or related engineering fields
- At least 3 years of experience in data analytics/science industry
- Experience in Micron Product Engineering or the semiconductor industry is preferred
- Demonstrate strong leadership and technical skills with a deep understanding of data analytics, data extraction, and analysis tools such as JMP, Tableau, and Power BI
- Excellent communication skills to present findings and insights to non-technical stakeholders
- Proven track record of collaborative work within/across teams to address sophisticated business and engineering problems
- Experience in mentoring and coaching team members to develop their skills
- Dedicated and highly motivated with a flexible approach towards adapting to different roles in a dynamic working environment
- Strong sense of responsibility and accountability towards assigned role with professional work ethic
- Work on site in Singapore with international travel to Taiwan