Yield Development Engineer

About the Role

Intel is seeking highly motivated individuals with strong technical backgrounds to drive continuous improvements in safety, quality, yield, reliability, cost, process stability/capability, and productivity. The role focuses on delivering analytical insights and driving yield improvement activities to minimize defects.

Key Responsibilities

• Perform detailed analysis to monitor inline yield and identify the root cause of defect and yield issues using statistical/data mining tools.
• Identify excursionary or baseline sources of defects or yield impacts and recommend/lead corrective actions.
• Lead/participate in continuous improvement projects on products and processes.
• Provide expertise on process flow segments.
• Lead/participate in multi-area problem-solving teams to troubleshoot complex yield problems.

Requirements & Tech Stack

Minimum Qualifications:

• Bachelor's degree in Materials Science and Engineering, Mechanical Engineering, Computer Science, Information Systems, Chemical Engineering, Electrical Engineering, Physics, or Chemistry, with 4+ years of hands-on experience in yield analysis, OR a Master's degree with 3+ years of experience, OR a Ph.D. with no prior professional experience.
• Experience with:
• Engineering analysis tools and scripting methods, including Python, JMP, and SQL.
• Analyzing big data and performing commonality analysis using data science libraries and dashboard creation.
• Root Cause Analysis, Model-based Problem Solving, and Commonality Analysis.

Preferred Qualifications:

• Experience in yield, integration, LYA (Layout Yield Analysis), FA (Failure Analysis), test, sort, defect metrology, or QNR.
• Proven experience leading cross-functional teams to solve yield-related challenges.
• Familiarity with wafer-level or package assembly processes or substrate process flow, including process flow, tools, and yield issues.
• Knowledge of semiconductor manufacturing processes and logic or substrate process flows required for yield analysis.

Ideal Candidate Traits

• Solid analytical skills and a passion for data analysis and problem solving.
• Proficiency in translating complex yield data into strategic action plans with clear milestones, accountability, and ownership.
• Effective communication and presentation skills.
• Excellent teamwork, leadership skills, problem solving, and prioritization skills.
• Organizational skills with attention to detail.
• Ability to thrive in a fast-paced environment with flexibility to meet tight product timelines.
• Strong drive for self-improvement and independently acquiring new technical skills.
• Ability to connect analysis results to process fundamentals, tool behavior, and physics principles.
• Adaptability in a fast-paced environment.

Work Model

• Eligible for a hybrid work model, allowing a split between on-site and off-site work.