Advanced Packaging Yield Analysis and Defect Engineer

Intel Intel · Semiconductors · Arizona, Phoenix, United States

Lead engineer for Advanced Packaging Technology and Manufacturing (APTM) Yield Group focused on driving yield and defect improvement. Responsibilities include extracting insights from large datasets using statistical methods and machine learning, developing solutions, and influencing the yield roadmap. Requires strong understanding of electrical/physical fails, defect metrology, and factory systems. Will lead a small group of engineers and partner with cross-functional teams.

What you'd actually do

  1. Extract insights from structured and unstructured data by quickly synthesizing large volumes of data, applying statistical methods and machine learning techniques
  2. Develop solutions to problems by utilizing formal education, knowledge of manufacturing process, statistical knowledge, and problem-solving tools
  3. Independently drive recommendations and influence the Yield and defects improvement roadmap
  4. Good understanding of the relationship between electrical and physical fails including a deep knowledge of FIFA, DFT, Sort/Test, Integration/Process Flow, Datamining, Databases, Data manipulation, and Data visualization
  5. Good understanding of Inline Defect Metrology, detection capabilities and underlying defect systems in the factory.

Skills

Required

  • Bachelor's degree (with 6+ years of relevant experience) OR Master's degree (with 4+ years of relevant experience) OR PhD degree (with 2+ years of relevant experience) in Materials Science and Engineering or Mechanical Engineering or Computer Science or Information Systems or Chemical Engineering or Electrical Engineering or Chemistry or Physics or any other related discipline
  • 5+ years of experience in data analysis through JMP, Python, or other data engineering software
  • US Citizenship Required and ability to obtain and maintain an active US Government clearance

Nice to have

  • Active US Government clearance
  • In-depth understanding and hands-on application of statistical analysis
  • Demonstrated proficiency in structured technical problem-solving
  • Demonstrated understanding of product design/circuit/architecture as relevant for yield analysis
  • Demonstrated understanding of inline metrology capabilities as relevant for yield analysis and defect systems

What the JD emphasized

  • US Citizenship Required and ability to obtain and maintain an active US Government clearance
  • 5+ years of experience in data analysis through JMP, Python, or other data engineering software

Other signals

  • Extract insights from structured and unstructured data by quickly synthesizing large volumes of data, applying statistical methods and machine learning techniques
  • Develop solutions to problems by utilizing formal education, knowledge of manufacturing process, statistical knowledge, and problem-solving tools
  • Good understanding of the relationship between electrical and physical fails including a deep knowledge of FIFA, DFT, Sort/Test, Integration/Process Flow, Datamining, Databases, Data manipulation, and Data visualization
  • Good understanding of Inline Defect Metrology, detection capabilities and underlying defect systems in the factory.