Computational Photography/Computer Vision Machine Learning Engineer, Camera & Photos
Apple Oakbrook
Weekly Hours: 40
Role Number: 200634411-0836
Summary
In the Camera Imaging Algorithms team in the Camera & Photos organization, we are looking for passionate, self-driven computational photography/computer vision machine learning engineers who enjoy both innovating down to the details and collaborating with broader cross-functional teams to bring exciting new imaging technology to our Apple products. We have worked on many core algorithms in the Apple camera imaging pipeline like Deep Fusion, Photonic Engine, SmartHDR, and Panorama. In this role, you will research and develop novel machine learning techniques for various image restoration and image fusion applications and contribute to shipping the most popular camera in the world.
Description
As a machine learning engineer on our team, you will contribute to algorithm design and implementation. You will develop and train deep learning models and collaborate with cross-functional teams like camera hardware, firmware, GPU, and image quality teams to bring your innovative ideas to product. We are seeking a creative and inquisitive engineer who can leverage their knowledge of classical computer vision and computational photography techniques to build deep learning models that help us design the next generation Apple camera imaging pipeline.
Minimum Qualifications
Strong coding skills in Python; experience in C/C++ a big plus
Demonstrated ability in developing machine learning algorithms for computational photography/computer vision and image processing problems
Extensive knowledge in camera processing pipeline, classical computer vision, and classical computational photography techniques
Experience with deep learning techniques for image restoration and image fusion applications (denoising/demosaicing/super-resolution), and experience with deep learning frameworks like PyTorch or TensorFlow
MS/PhD in Computer Vision, Machine Learning, Computer Science, Electrical Engineering or related fields
Preferred Qualifications
Excellent verbal and written communication skills
Creativity and curiosity for solving complex problems.
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