Computer Vision Software Engineer at Apple
Cupertino, California, United States -
Full Time


Start Date

Immediate

Expiry Date

18 May, 26

Salary

0.0

Posted On

17 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Computational Photography, Computer Vision, Image Processing, Machine Learning, C, C++, Camera Pipeline, 3D Geometry

Industry

Computers and Electronics Manufacturing

Description
iPhone is the most popular camera in the world, with billions of photos taken every year. The seamless integration of software and hardware has led to camera features like the Photonic Engine, Portrait mode, and Super-high-resolution photos, which deliver magical experiences that surprise and delight our customers! The Camera Technologies & Systems team in the Camera & Photos org delivers amazing quality photos and videos by combining state of the art computer vision, image processing, and machine learning. DESCRIPTION As an engineer on our team you'll develop and extend those software features, working side-by-side with the exceptional engineers who made iPhone’s camera what it is today, and build new extraordinary camera capabilities spanning the universe of Apple devices. Whenever you see a “Shot on iPhone” billboard, you see our work; it could be your work, too! MINIMUM QUALIFICATIONS Strong background in computational photography. Knowledge and experience using Computer Vision to solve real-world problems. Experience with camera pipeline. Excellent coding skills in C or C++. Strong verbal and written communication skills. MS/PhD in Computer Vision, Machine Learning, Computer Science, Electrical Engineering PREFERRED QUALIFICATIONS Familiarity with multiple-camera systems and 3D geometry. Experience with Machine Learning
Responsibilities
Engineers on this team will develop and extend software features for camera technologies, working alongside exceptional engineers to build new camera capabilities across Apple devices. This involves combining state-of-the-art computer vision, image processing, and machine learning to deliver high-quality photos and videos.
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