Computational Imaging & Machine Vision Engineer (Internship or Full-time) | Apple

Oct. 23, 2022

Location: Cupertino, CA

Apple’s Image Science team, a subgroup of Camera Hardware & Depth, develops novel calibration, simulation and metrology processes to enable both machine-vision-driven and photographic experiences, delivering multi- camera calibration as used in Portrait Mode, Cinematic Video, and many other flagship features, as well as shaping feature specifications for future use cases and hardware.

The team is seeking a camera engineer with a diverse skillset to develop high-volume calibration software enabling AR/VR features, amongst others, and physics-based methodologies for informing the design and architecture of next-generation hardware products and software features.

Key Qualifications

  • Expertise with lens-based imaging systems and camera calibration methods
  • Experience with projective geometry, geometric imaging optics and multi-camera epipolar geometry
  • Expertise with computational imaging algorithms, computer vision and image processing
  • Experience with numerical methods, applied mathematics and statistics
  • Experience with loss function selection for computer vision and computational photography applications
  • Expertise with scripting languages (e.g. Python, MATLAB)
  • Experience with C/C++ programming languages
  • Experience with Machine Learning techniques and familiarity with deep learning frameworks (e.g. Pytorch, JAX, TensorFlow)
  • Ability to learn quickly and think deeply across various technical areas
  • Ability to collaborate, communicate and lead across groups; excellent interpersonal skills

Role and Responsibilities:

  1. Defining and delivering camera calibration roadmap and test strategy based on systems architecture, feature requirements and statistical analyses;
  2. Simulating and modelling imaging optics and projective geometry to define use case specifications and camera calibration and modelling requirements;
  3. Physics-based camera algorithm and software development, packaging and cloud deployment;
  4. Characterizing end-to-end (hardware and software) performance of features through simulation studies;
  5. Frequent collaboration with cross-functional teams in software, firmware, test engineering and operations; skillfully exerting influence in areas outside of sphere of control;
  6. Managing project deliverables and schedules to meet commitments to product development teams.