Machine Learning Video Algorithms Engineer
Santa Clara Valley (Cupertino), California, United States
Imagine the impact you can make. A billion users will use the technologies you helped craft almost daily. At Apple, you will have the opportunity to work on products that are always leaders in the industry and occasionally, change the world! The Video Engineering group at Apple is responsible for creating the Camera, Image and Video core technologies used in all Apple products and services. We are looking for a Applied machine learning engineer/researchers in the area of content understanding, computer vision, media data compression and processing, deep learning and more. We are looking for a highly self-motivated and enthusiastic individual, who is able to excel in a technically challenging environment, to fill in the position of video algorithm engineer.
- Expert knowledge of the principles, algorithms, and techniques and hands-on experience in machine learning, computer vision, video and image signal processing.
- Excellent software design, problem solving, and debugging skills
- Solid C/C++ programming skills.
- Good written and oral communication skills
- Knowledge and experience in video compression standards, such as H.264, HEVC, AV1, VP9, VVC are a big plus
In this role you will research and develop cutting edge machine learning models for content understanding, computer vision and media data compression and processing. This position requires a highly self-directed individual with strong creative and analytic skills as well as excellent communication skill, because you are expected to work with the larger machine learning community within Apple. Your responsibilities include, but not limited to: 1. Invent and implement new algorithms or machine learning models for content understanding, computer vision and media data compression and processing. 2. Optimize the algorithms and models so that they can be efficiently realized on Apple products. 2. Work with other hardware/software architects to define and implement media features and algorithms for future products. 3. Spearhead R&D in learning-based and other upcoming new media technologies.
Education & Experience
MS/PhD in Electrical Engineering or Computer Science