About The Position

As part of Apple's Camera Technologies group, the Image Scientist will help design innovative technology for camera systems, from sensor to lens. This role involves researching, designing, developing, and qualifying camera hardware for Apple products to create a magical photography experience. The Image Sciences team, within the Camera Hardware and Depth Team, focuses on developing novel metrology, calibration, and simulation processes for machine-vision-driven and photographic experiences. They collaborate with cross-functional teams to define hardware design specifications and key performance metrics. The team is looking for an expert in imaging, computer vision, or rendering to develop next-generation, high-throughput simulation frameworks to guide product design and architecture, including AR/VR features.

Requirements

  • BS in Optics, Physics, Electrical Engineering or related field.
  • Programming experience in at least one of the coding languages: C, C++, Python, or Matlab.
  • Experience with one or more of the following: Optics: imaging system design, Computer Vision, computational imaging, or similar.
  • Experience with algorithms for image quality enhancement.

Nice To Haves

  • MS/PhD degree in Optics, Physics, Electrical Engineering or related field and relevant industry experience in Optics or Image Signal Processing.
  • Experience in project management and/or driving projects independently in ambiguous problem spaces.
  • Published research in imaging, computational photography, or computer vision.
  • Experience with camera sensor physics, noise modeling, or radiometry.
  • Experience with synthetic data generation for ML training pipelines, model optimization and/or deployment, related to imaging and data analyses.
  • Experience with GPU computing (CUDA, OpenCL) or distributed processing at scale.

Responsibilities

  • Design, develop, and maintain high-throughput simulation frameworks to generate large volumes of synthetic imagery on-demand.
  • Build and refine models of camera systems—from sensor to lens—to simulate real-world imaging performance.
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