Camera Image Processing Engineer

Socket.dev; Cupertino (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Apple is seeking an Image Processing Engineer to help analyze raw sensor data and clean up images, enabling higher quality photos on hardware and software teams. You will propose novel algorithms for camera pipelines and ensure robust performance on Apple silicon.

The role emphasizes working on GPU-based image processing, ML algorithms, and optimization for the Apple Neural Engine, with a focus on rapid learning and strong engineering judgment.

Qualifications

• Strong programming skills on Apple platforms (Swift, Metal, Objective-C).
• Experience implementing image processing algorithms on GPUs.
• Exposure to machine learning applied to image processing.
• Advanced degree (M.S. or Ph.D.) in Imaging/Color/Vision/Optics/EE with 3+ years in related field.

Responsibilities

• Analyze raw sensor data and identify issues; propose algorithms to address problems.
• Fix problems arising from sensors, optics or control systems (auto focus, IS).
• Develop and optimize traditional ML algorithms running on Apple Neural Engine (ANE).

Skills

Swift

Metal

Objective-C

GPU programming

Image processing

Machine learning

GenAI tooling

Education

M.S./Ph.D. in Imaging/Color/Vision/Optics/EE

Tools

Apple Neural Engine (ANE)

Job 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. As an Image Processing Engineer, you will help to take raw data off our camera sensors, and clean up the image, giving our industrial design teams more freedom when designing our hardware, confident that your work will still give a high quality image in the end.

Description

We are looking for candidates with some basic image processing experience, and some familiarity with writing code on GPUs. In this role you will help to analyze raw sensor data, identify issues, and propose algorithms to handle any problems. You can be called upon to fix problems arising from sensors, optics or control systems (such as auto focus and optical image stabilization). As such we do not expect you to be an expert on these things - there are too many to know them all! But we are looking for candidates with a demonstrated capability for creative thinking and quick learning. We increasingly use GenAI tools to help accelerate coding, but every change goes through a human review layer, so strong engineering judgment matters as much as raw output. Our team also designs traditional ML algorithms that run directly on the Apple Neural Engine (ANE).

Minimum Qualifications

Strong programming skills, particularly on Apple platforms - notably Swift, Metal, and Objective-C.Some experience with image processing algorithms implemented on GPUs.Graphics programming experience - comfortable working directly with pixels.Exposure to machine learning, particularly as applied to image processing.M.S. or Ph.D. in Imaging, Color, Vision, Computer, Optics Science, EE, or equivalent with 3+ years of experience in a related field.

Preferred Qualifications

An understanding of photography and what makes an image look good or bad. Photography in challenging conditions, such as low-light or high movement is particularly useful.Experience with an existing camera image processing pipeline.Strong experience with optimizing GPU workloads to run efficiently.Experience with performance-oriented, high-throughput compute.A demonstrated track record of algorithm development - solving novel problems rather than applying known recipes.Experience designing or deploying traditional ML algorithms that run on the Apple Neural Engine (ANE).