At Intel, the Foundry Technology Development (TD) unit is the driving force behind Moore's Law, enabling us to create groundbreaking technology that enriches lives globally. Within Intel Foundry TD, our Logic Technology Development (LTD) organization is at the forefront of creating and refining each process technology node. The LTD organization is seeking a Yield Development Engineer with a focus on design analytics to develop, implement, optimize, maintain, and document procedures for design database analysis supporting metrology equipment used for development and manufacturing for foundry customers. 

In this role, your responsibilities will include:   

• Develop methods, processes, and systems to consolidate and analyze diverse products, establishing optimal methodologies for defect mode detection, understanding, and yield modeling. 

• Organize, interpret, and structure insights from fab process, defect, and electrical data, detect data anomalies, and drive process changes for yield enhancement. 

• Extract insights from structured and unstructured data by synthesizing large volumes of data and applying statistics, machine learning, and coding techniques. 

• Develop systems to transform complex experimental and manufacturing data into yield improvement actions using knowledge of product design and test features. 

• Ensure manufacturability over process and product design, working with computational and modeling technology to highlight process and spec corners. 

• Execute new product introductions with prompt turnaround, enable design technology co-optimization, and participate in design of experiments in factory task forces. 

• Develop tools, multivariate algorithms, and methodologies to perform high-volume data analysis to identify root cause yield limiters and key process changes. 

• Develop measurement recipes to provide quick and accurate feedback on product integrity. 

• Develop computational tools and AI/ML applications to improve patterning solutions, decrease process debug time, and improve design efficiency. 

• Work on solution exploration, technical design, implementation, deployment in a production environment, and maintenance of deployed solutions. 

• Create innovative solutions to problems, collaborate with internal teams to ensure data integrity, implement custom algorithms, and develop efficient software solutions. 

• Debug software-related issues in the production environment, occasionally requiring off-hour urgent support. 

You must possess the below minimum education requirements and minimum required qualifications to be initially considered for this position. Relevant experience can be obtained through schoolwork, classes, project work, internships, and/or military experience. Additional preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.  

Minimum Qualifications:   

• Bachelor’s Degree with 4+ years of experience, OR Master’s Degree with 3+ years of experience or PhD, in Engineering, Physics, Material Science, Computer Science, or related STEM field with software focus.  

• 2+ years of relevant experience in Programming (C++/Python/SQL), data analysis, DB architecture, and/or dataflow development, GitHub, semiconductor devices and circuits, semiconductor device physics, or semiconductor product design. 

• Ability to obtain and maintain an Active US Government Top Secret (TS) Security Clearance with SCI access. 

• US Citizenship required. 

This position is not eligible for Intel immigration sponsorship. 

Preferred Qualifications: 

• Active US Government Security Clearance. 

• Experience with data analysis systems and software tools. 

• Expertise in semiconductor physics and processing. 

• Experience in semiconductor product design and infrastructure. 

• Demonstrated experience with Statistical Process Control (SPC) or Design of Experiments (DOE) principles. 

• Experience working with external and internal partners. 

• Experience with data structure libraries (e.g., Immutable.js). 

• Experience in data systems infrastructure for big data applications