Experienced Defect Product Module Engineer

Samsung is a world leader in advanced semiconductor technology, founded on the belief that the pursuit of excellence creates a better world. At Samsung Austin Semiconductor, we are Innovating Today to Power the Devices of Tomorrow. Come innovate with us!

We are looking for a highly technical Defect Engineer to join our cutting-edge fabrication facility in Taylor, Texas. Unlike traditional defect management, this role focuses on the strategic quantification of yield-impacting defects and the long-term reduction of the factory’s baseline defect trends. You will be the Subject Matter Expert (SME) for a specific module (portion of the manufacturing line), bridging the gap between raw inline defect data and final wafer yield.

By leveraging advanced data analysis and defect characterization, you will work with predictive models to forecast yield loss and drive the technical roadmap required to hit aggressive factory yield targets. This is a high-impact role for an engineer who enjoys data analysis and uncovering hidden signals and patterns in big data to drive physical process improvements.

Here’s What You’ll Be Responsible For:

• Baseline Yield Optimization:
  Quantify the impact of specific defect types on final yield and drive systematic actions to reduce the baseline defect density across the manufacturing flow.
• Yield Prediction Modeling:
  Improve predictive models that correlate random inline defects to final yield loss, providing the factory with early warning signals of yield degradation.
• Defect Characterization:
  Perform deep-dive characterization of defects (using SEM, TEM, or EDX) to link physical defect signatures to specific process failures within your assigned module.
• Module Subject Matter Expertise:
  Serve as the primary SME for your assigned module, providing technical guidance to process and equipment engineers on which tools and processes to focus on to drive yield improvement.
• Strategic Roadmap Development:
  Define and drive the strategy for yield improvement, executing to quarterly and annual targets and tracking progress against factory-level yield goals.
• Data-Driven Analysis:
  Utilize large datasets to perform spatial analysis (wafer maps) and temporal analysis to identify causes for yield variation.
• Cross-Functional Collaboration:
  
  Partner with Process Integration and Failure Analysis engineers to determine the "killer" vs. "non-killer" status of defects to ensure engineering efforts are focused on the highest-ROI improvements.

Here’s what you’ll need:

• Minimum:
  Bachelor’s Degree in Materials Science, Electrical Engineering, Chemical Engineering, Mechanical Engineering or a related STEM field.
• Semiconductor Process:
  Broad semiconductor knowledge including different types of materials used during the manufacturing process, process tool theory of operations/or hands on experience, and general semiconductor process knowledge.
• Advanced Data Analytics:
  Expert proficiency in JMP, Spotfire, or, Python is highly preferred for statistical modeling and data mining.
• Statistical Mastery:
  Strong understanding of Design of Experiments (DOE) and ANOVA to validate yield improvement actions.
• Defect Detection Methodology:
  Familiar with Metrology tool models and capabilities for defect inspection and when different strategies are used for specific types of defects.

The current base salary range for this role is between $95,000 - $120,000. Individual base pay rates will depend on factors including duties, work location, education, skills, qualifications and experience. Total compensation for this position will include a competitive benefits package and may include participation in company incentive compensation…