Intel Foundry Module Development Engineer

Intel Intel · Semiconductors · Oregon, Hillsboro, United States

This role focuses on developing semiconductor manufacturing processes, designing and analyzing experiments for new technologies, and integrating manufacturing steps. It involves leading scientific research for device architectures and ensuring technologies meet manufacturing requirements.

What you'd actually do

  1. Led scientific research enabling the manufacture of innovative device architectures coupled with the realization of these architectures.
  2. Designing, executing, and analyzing experiments necessary to meet engineering specifications for their process.
  3. Participate in the development of intellectual property.
  4. Integrate the many individual steps necessary for the manufacture of complex microprocessors.
  5. Ramp to manufacturing volumes to demonstrate the technology meets requirements while simultaneously transferring the technology to counterparts in manufacturing via the Copy Exactly Methodology.

Skills

Required

  • Master's degree with 5+ years of experience OR PhD with 1+ years of experience in Materials Science, Chemical Engineering, Chemistry, Physics, Mechanical Engineering, Electrical Engineering, or a related Scientific STEM field of study
  • hands-on experimental research

Nice to have

  • 4+ years of Semiconductor Industry experience in one or more of the following areas: Semiconductor processing, Semiconductor fabrication, or nanotechnology.
  • Semiconductor processing or device fabrication and/or nanotechnology with a wet etch
  • Strong expertise in chemical processing and chemical development
  • Experience leading projects and leading cross-functional teams.
  • Process control systems, methodologies, sources of variability, and statistics.

What the JD emphasized

  • hands-on experimental research
  • Semiconductor Industry experience
  • Semiconductor processing
  • Semiconductor fabrication
  • nanotechnology
  • chemical processing
  • chemical development
  • Process control systems
  • methodologies
  • sources of variability
  • statistics