Machine Learning Video Codec Algorithm Engineer

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. We are seeking a highly motivated and hardworking individual with a passion for solving technical challenges to join our team as a Video Codec Algorithm Engineer. As part of a small and dynamic group, you will play a key role in contributing to video codec standards and developing ground breaking video compression and processing algorithms for current and future Apple products. This role demands a dedicated individual with strong analytical and creative problem-solving skills, as well as a deep passion for video coding and processing technologies. Orchestrate R&D in emerging media compression technologies and standards. Design and implement innovative video compression/processing algorithms optimized for existing hardware. Collaborate with hardware and software architects to define and integrate media features and algorithms for future products.BS and a minimum of 10 years relevant industry experience. Expertise in video and image coding principles, algorithms, and techniques. In-depth knowledge of video compression standards such as H.264, HEVC, VVC, VP9, AV1, and AV2. Strong programming skills in C/C++. Excellent software design, problem-solving, and debugging abilities.PhD or MS in Computer science, Electrical Engineering, or related major. Experience with both objective and subjective visual quality assessment methods. Understanding of hardware-based techniques with the ability to develop ideas that are hardware-friendly. Familiarity with video processing algorithms (e.g., scaling, noise reduction, tone mapping). Proficiency in digital signal processing and information theory. Knowledge of the latest computer vision and deep learning technologies. Excellent collaboration skills. Strong written and verbal communication skills.