THE ROLE:

You will be supporting the development and launch of high-quality AI , Graphics, CPU, APU, and custom design products in the Product Yield Engineering team. You will optimize manufacturing costs and ensure timely market delivery. You will be involved in cross-functional collaboration with engineering, design, foundry, and data teams to resolve complex challenges, accelerate product ramp-up, and drive ongoing yield improvements.

KEY RESPONSIBILITIES:

• Data analysis and yield engineering, focusing on post-testing data, presentation, and understanding fabrication/testing processes
• Analyzing data across various products
• Manage product wafer costs, including yield and test content, to meet quality and yield targets
• Analyze yield metrics to forecast supply and product performance
• Implement best practices for test and characterization
• Use diagnostics and failure analysis to reduce defects in foundry environments
• Collaborate with internal and external foundry teams to identify and implement process improvements
• Engage with engineering, product teams and business units to define and achieve program requirements for defectivity, power, performance, reliability, and quality

PREFERRED EXPERIENCE:

The ideal candidate will have the following minimum skills:

• Minimum 7 years of experience in process technology or product development, preferably with leading-edge foundries, assembly, and test operations.
• Direct experience in JMP or equivalent data analysis tools.
• Database querying and SQL
• An advanced degree in a related field may reduce the minimum experience requirement

In addition, we value these technical competencies in our team:

• Strong AI-forward data science skills with experience in big data models, databases, and machine learning
• Strong scripting capability including using AI to extract and automate complex data analysis
• Understanding of functional and design-for-test methodologies, structures, and practices
• Technical expertise in the productization of new and advanced technologies
• Knowledge of leading edge (FinFET, GAA, etc.) semiconductor device physics
• Semiconductor manufacturing experience
• Ability to work effectively in geographically distributed and diverse teams

ACADEMIC CREDENTIALS:

• Bachelor's Degree in Electrical Engineering, Computer Engineering, or Computer Science, or a related degree in Math, Sciences, or Statistics.