APTM Yield Analysis/Device Engineer

At Intel, we create world-changing technology that improves the life of every person on the planet. By joining the Advanced Packaging Technology and Manufacturing (APTM) Yield Group, you will be part of a team tasked with the critical objective of driving yield and defect improvement across our entire advanced packaging portfolio. We solve highly complex physical and electrical problems to ensure our latest packaging technologies successfully transition from development into high-volume manufacturing.

We are seeking a APTM Yield Analysis/Device Engineer to drive technology development, transfers, and manufacturing ramps in Rio Rancho, New Mexico. In this role, you will analyze massive, multi-dimensional datasets to identify where manufacturing processes, test content, and inline metrologies must be optimized. Acting as a strategic technical advisor, you will set clear engineering priorities, lead cross-functional problem-solving initiatives, and directly influence our technology yield roadmap.

• →Data Synthesis & Insight Extraction: Extract insights from structured and unstructured factory datasets using statistical methods, machine learning, and tools like JMP or Python.
• →Failure Correlation: Correlate electrical and physical failure mechanisms by utilizing deep knowledge of Failure Analysis (FIFA), Design for Test (DFT), Sort/Test, and Integration/Process flows.
• →Defect System Optimization: Manage inline defect metrologies, evaluate detection capabilities, and drive inline defect reduction programs across the factory.
• →Technical Program Leadership: Lead a small group of engineers (direct or indirect) to execute experiments, resolve nonstandard yield events, and ensure smooth technology transfers to High-Volume Manufacturing (HVM).
• →Stakeholder Reporting & Collaboration: Deliver detailed technical reports summarizing yield and device health to upstream and downstream partners, establishing clear action plans to achieve best-in-class yield levels.

• Leadership & Cross-Functional Influence: Instills a high-performing team culture with a willingness to lead, guide, and collaborate across diverse organizational boundaries.
• Tolerance for Ambiguity & Flexibility: Adapts rapidly to changing priorities, new technical fields of study, and fluctuating business demands.
• Strategic Prioritization & Autonomy: Works with minimal direct oversight to prioritize critical path items and resolve complex, unstructured technical issues.
• Executive Communication: Delivers concise, high-impact technical presentations to influence decision-making among diverse groups at all levels.

Apply today to join Intel New Mexico's APTM Yield Group and lead the technical breakthroughs that power global computing. Let's build the future together.

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Experience would be obtained through a combination of prior education level classes, and current level school classes, projects, research and relevant previous job and/or internship experience.

• Bachelor's degree in Materials Science, Mechanical Engineering, Computer Science, Information Systems, Chemical Engineering, Electrical Engineering, Chemistry, Physics, or a related technical discipline with 5+ years of semiconductor industry experience.
• OR Master's degree in a matching discipline with 3+ years of semiconductor industry experience.
• OR PhD in a matching discipline with 1+ years of semiconductor industry experience.

• 2+ years of experience in:
  • JMP, Python, or alternative data engineering software for statistical data analysis.
  • Applying statistical analysis to high-volume manufacturing data.
  • Utilizing structured technical problem-solving methodologies (e.g., Model-Based Problem Solving).
  • Linking product design, circuit architecture, or DFT to yield analysis.
  • Working directly with inline defect metrology equipment or defect classification systems.

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