Machine Learning Video Engineer

Apple·Cupertino, California, United States·posted 1h ago · last seen 47m ago

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About interviewing at Apple

One of tech's least standardized loops: you interview for a specific team, and every stage belongs to it. Recruiter/hiring-manager screen, one to three 45–60 minute Coderpad coding screens, a system design round shaped by Apple's reliability and privacy constraints, and a behavioral round — then a panel debrief. There is no central question bank; questions map to the team's real stack.

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Description

Summary

Want to work on cutting edge technology that keeps the customer front and center? The Video Engineering group at Apple is responsible for creating the image/video core technologies used in almost all Apple products and services. As a machine learning engineer, you’ll be developing machine learning based technologies for the image and video domain. As a member of a fast-paced team, you will also have the unique and exciting opportunity to shape upcoming products that have direct customer impact and will delight and inspire millions of people every day!

Description

This role requires an independent, self-motivated, and creative engineer with deep expertise in machine learning, coupled with a strong understanding of video and image processing quality. Your primary focus will be applying cutting-edge machine learning techniques to complex image and video challenges to create customer impact across current and future Apple products. In this role, you’ll work both independently and collaboratively with team members to prototype innovative deep learning applications for video processing, presenting and demonstrating your work to cross-functional teams and leadership alike. You’ll be responsible for designing sophisticated model architectures, fine-tuning performance parameters, and implementing architectural modifications to enhance overall output quality. Working closely with the team, you’ll focus on seamlessly porting solutions across different platforms while optimizing models for memory efficiency, power consumption, and processing speed to balance quality in operating constraints. Additionally, you’ll strategically distribute computational workloads across CPU, GPU, Apple Neural Engine, and other specialized hardware components to develop robust, viable solutions.

Minimum Qualifications

BS and a minimum of 3 years relevant industry experience Excellent fundamentals in machine learning Knowledge of Video or Image processing or Computer Vision Solid programming skills for common ML frameworks like PyTorch or TensorFlow

Preferred Qualifications

Experience in prototyping models for edge devices through quick iterations Familiarity with productization flow for ML models Prior experience working on deep learning techniques for video processing / computer vision. Strong fundamentals in Computer architecture Good written and oral interpersonal skills

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