Photonics Design Engineer

Apple•Cupertino, CA

About The Position

As a Photonics Design Engineer within the Camera Semiconductor Devices organization, you will focus on exploring and developing advanced photonic devices for future applications. In this fast-paced, proactive role, you will lead large-scale computational modeling and machine learning driven design workflows, collaborating closely with cross-functional teams and external vendors to bring next-generation optical components from concept to production. You will manage end-to-end device simulation and evaluation, using data-driven insights to clearly communicate engineering risks and architectural merits to facilitate strategic decision-making.

Requirements

  • B.S. degree in Electrical Engineering, physics, applied mathematics, Computational Sciences or an equivalent field.
  • Experience in semiconductor and photonic device design & development and data analysis.
  • Experience in electromagnetics modeling, inverse design and/or Machine Learning

Nice To Haves

  • M.S./Ph.D. degree in Electrical Engineering, physics, applied mathematics, Computational Sciences or an equivalent field.
  • 3+ years’ experience with in-depth understanding and proficiency in electromagnetics modeling, inverse design and Machine Learning.
  • Familiar with semiconductor device physics with experience in device design and development, data analysis and problem-solving skills.
  • Possesses a strong aptitude to learn with a proactive attitude and to resolve challenges independently, passionate about taking responsibilities and driving for results, and excellent in teamwork and communication.

Responsibilities

  • Exploring and developing advanced photonic devices for future applications.
  • Leading large-scale computational modeling and machine learning driven design workflows.
  • Collaborating closely with cross-functional teams and external vendors to bring next-generation optical components from concept to production.
  • Managing end-to-end device simulation and evaluation.
  • Using data-driven insights to clearly communicate engineering risks and architectural merits to facilitate strategic decision-making.
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