Intel Foundry Ltd Yield Development Engineer

Intel Intel · Semiconductors · Oregon, Hillsboro, United States +1

This role focuses on developing AI/ML applications and computational tools to improve semiconductor manufacturing yield. The engineer will analyze diverse data sources, perform statistical and machine learning analysis, and develop algorithms to identify root causes of yield limiters and recommend process improvements. The role involves working with big data, statistical analysis, and machine learning techniques to enhance manufacturability and yield across technology nodes.

What you'd actually do

  1. Develop methods, processes, and systems to consolidate and analyze diverse big data sources for defect mode understanding and yield modeling.
  2. Perform statistical analysis, create visualizations, and construct process development roadmaps that drive technology yield milestones.
  3. Extract insights from structured and unstructured data using advanced statistics, machine learning, and coding techniques.
  4. Develop multivariate algorithms and tools to identify root cause yield limiters and recommend process changes for yield improvement.
  5. Develop AI/ML applications and computational tools to bridge the gap between design and manufacturing, improve design efficiency, and reduce debug time.

Skills

Required

  • Ph.D. in semiconductor science-related STEM degree
  • advanced semiconductor devices and process flow
  • data analysis systems and software tools
  • yield projection
  • machine learning
  • statistical analysis
  • coding techniques

Nice to have

  • project/program management
  • strong self-initiative
  • self-learning capabilities
  • working across organizations through matrix structures

What the JD emphasized

  • Ph.D. in semiconductor science-related STEM degree
  • advanced semiconductor devices and process flow
  • data analysis systems and software tools
  • yield projection
  • AI/ML applications

Other signals

  • Develop AI/ML applications and computational tools to bridge the gap between design and manufacturing
  • Extract insights from structured and unstructured data using advanced statistics, machine learning, and coding techniques
  • Develop multivariate algorithms and tools to identify root cause yield limiters and recommend process changes for yield improvement