About the role
AI summarisedJoin an inclusive team dedicated to relentless innovation in memory and storage solutions. This role focuses on applying advanced data analytics, machine learning, and AI to enhance product quality, improve yields, and drive reliability within the High Bandwidth Memory (HBM) group.
IDMOnsiteHIG
Key Responsibilities
- Develop, validate, and deploy product-disposition solutions (wormhole) to reduce Defects Per Million (DPM).
- Utilize statistical tools, machine learning, and AI for engineering data analysis to enhance yields and reliability.
- Create a deviation alert system to monitor yield loss, characteristic/parameter trends, and wafer/die/cube shading.
- Develop state-of-the-art algorithms, including ML and DL models, for data mining, pattern recognition, and quality enhancement.
- Collaborate with cross-functional teams (Fab, HBM Technology Development, Design, Quality/Reliability) for holistic product development.
- Act as an AI/ML advocate, deploying and validating models to enhance KPIs like Quality, Cost, Cycle Time, and Scale.
- Mentor and develop team members to foster organizational growth.
Requirements
- Bachelor's or Master's degree in Electrical and Electronics Engineering, Statistics, or related engineering fields.
- Demonstrated experience in data analytics/science industry.
- Strong leadership and technical skills with deep understanding of data analytics and extraction tools.
- Proficiency in presenting complex findings to non-technical stakeholders.
- Proven track record of collaborative problem-solving across engineering teams.
- Experience in mentoring and coaching team members is required.
- Highly motivated with flexibility to lead technical programs or guide teams.
- Strong sense of responsibility and professional accountability.