iPhone is the most popular camera in the world, with billions of photos captured every year. The seamless integration of software and hardware has led to breakthrough camera features — from the Photonic Engine and Portrait mode to Super-high-resolution photos — delivering magical experiences that surprise and delight our customers.\\nThe Camera Technologies \u0026 Systems team in the Camera \u0026 Photos org delivers amazing quality photos and videos by combining state of the art computer vision, image processing, and machine learning.
As an engineer on our team, you will design, develop, and ship the software features that define Apple"s camera experience — working side-by-side with the exceptional engineers who made iPhone"s camera what it is today. You"ll build extraordinary new camera capabilities that span the full universe of Apple devices. Whenever you see a \\"Shot on iPhone\\" billboard or press the shutter on your iPhone, you see our work — and it could be your work, too.
Design, implement, and optimize real-time and near-real-time Computer Vision and video processing algorithms for Apple silicon.\\nPrototype novel computational photography and computer vision features from concept through production.\\nCollaborate closely with cross-functional partners across software, hardware, silicon, and algorithm teams to co-develop groundbreaking camera technologies.\\nDevelop evaluation frameworks, metrics, and analysis tools to measure and continuously improve image and video quality.
Strong proficiency in C/C++ and Objective-C/C++; working knowledge of Python for prototyping and analysis.\\nExperience debugging and profiling on resource-constrained or embedded mobile platforms.\\nDomain expertise in computer vision, computational photography, or machine learning — with hands-on implementation experience.\\nFamiliarity with modern camera or video processing pipelines.\\nExcellent verbal and written communication skills
Experience with GPU programming using Metal, OpenCL, or CUDA.\\nTrack record of shipping camera, imaging, or video features in production systems.\\nThrives in a highly collaborative, cross-functional environment.\\nMS or PhD in Computer Science, Electrical Engineering, Computer Vision, Machine Learning, or a related field.