About the role

AI summarised

The Staff Yield Engineer – Data Analytics at AMD supports the development and launch of high-quality AI, Graphics, CPU, APU, and custom design products by optimizing manufacturing costs and ensuring timely market delivery. The role involves analyzing post-testing and product data, managing wafer costs, forecasting supply and performance, and collaborating with engineering, design, foundry, and data teams to drive yield improvements and resolve complex challenges. The position requires strong data science, scripting, and semiconductor manufacturing expertise, with a focus on advanced technologies and geographically distributed teamwork.

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Key Responsibilities

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

Requirements

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