Aptm Yield Analysis/device Engineer

Intel Intel · Semiconductors · New Mexico, Albuquerque, United States

This role focuses on yield analysis and improvement in advanced packaging technology and manufacturing. The engineer will extract insights from large datasets using statistical methods and machine learning techniques, develop solutions to manufacturing process problems, and influence the yield improvement roadmap. The role requires understanding the relationship between electrical and physical fails, inline defect metrology, and collaborating with various engineering 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 Independently drive recommendations and influence the Yield improvement roadmap
  3. 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.
  4. Good understanding of Inline Defect Metrology, detection capabilities, and underlying defect systems in the factory.
  5. Owning determining the actions required to deliver Best in Class yield levels. Developing solutions to problems using process, Sort/Test and inline metrology knowledge, statistical knowledge, and problem-solving skills.

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, Mechanical Engineering, Computer Science, Information Systems, Chemical Engineering, Electrical Engineering, Chemistry, Physics, or a closely related field.
  • Data analysis using JMP, Python, or other data engineering and analytics tools.

Nice to have

  • 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.

What the JD emphasized

  • applying statistical methods and machine learning techniques
  • statistical knowledge
  • statistical analysis
  • structured technical problem-solving

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
  • Owning determining the actions required to deliver Best in Class yield levels