Research Engineer - Video Tone Mapping

Apple's Camera Algorithm team is looking for extraordinary engineers and researchers interested in developing next generation of image capture, processing and rendering algorithms to be used across all Apple product cameras! As part of the team you will research and develop novel ways to improve the image and video quality of Apple's camera systems. In order to reduce the computational complexity of your methods you are encouraged to take advantage of Apple silicon technologies such as the Image Signal Processor (ISP) or the Apple Neural Engine (ANE). The Camera Algorithm Tone Mapping team works at the intersection of software and hardware, developing real time algorithms required for camera operation, and has major impact on the final image and video quality! The team has a history of delivering solutions running on Apple products, for example Smart HDR, HDR video tone mapping or Apple Log encoding. This interdisciplinary team works closely with many other groups including silicon design, camera hardware and camera software teams to deliver industry leading consumer imaging devices. The work environment champions innovation, rapid iteration and awards independence and creativity in solving engineering problems.

As an algorithm developer you will be responsible for crafting the creative look of videos captured with Apple cameras by developing capture side tone mapping algorithms. You will drive algorithm development across all stages of the cycle; from the initial idea and proof of concept work through on-device implementation all the way to field testing, validation and finally surprising and delighting our customers.

MS and a minimum of 10 years relevant industry experience.\nTrack record of developing image processing algorithms for example: auto white balance, tone mapping, auto exposure and high dynamic range capture.\nValidated coding skills in Python or MATLAB.

Familiarity with a digital camera image processing pipeline and the Image Signal Processor (ISP).\nUnderstanding of image quality metrics and subjective evaluations.\nProven knowledge of HDR encoding standards.\nPrior experience with professional video content postproduction and color grading workflows.\nCuriosity about vision science and/or color science.\nProgramming skills in C/C++.\nExposure to machine learning algorithms.\nPassion for photography and videography.