Machine Learning Video Algorithms Engineer
- San Diego, CA
Posted: Aug 6, 2021
Role Number: 200200454
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 crafting the image/video core technologies used in almost all Apple products and services. We are looking for a highly self-motivated and enthusiastic individual, who is able to excel in a technically meaningful environment, to fill in the position of video algorithm engineer.
- Excellent problem solving skills
- Expert knowledge of the principles, algorithms, and tools of deep learning, including models, training strategies, training dataset building, cost functions, quality metrics, etc...
- Expert knowledge of the principles, algorithms, and techniques in video/ image processing, and low-level computer vision, such as spatial scaling, optical flow estimation, segmentation, frame rate up conversion, noise reduction, color processing, etc...
- Excellent written and oral communication skills
- Proven programming skills using common ML tools such as Python, PyTorch, CUDA Metal, and C/C++
In this role you will work together with colleagues in a fast-paced environment, developing ML-based video processing solutions for current and future Apple products. This position requires a highly self-directed individual with strong creative and analytic skills, and a passion for applying deep learning technologies in video processing and low level vision tasks. Your responsibilities include, but are not limited to: 1. Working with our own team as well other teams, on developing a DL-based solution for a video processing/low level vision problem, building training dataset, training the DL model, prototyping and demonstrating to leadership. 2. Working with multi-functional teams on implementing the solution on iOS/macOS platforms, including DL model simplification and retraining, model porting, code integration, performance acceleration, power tuning, quality tuning, etc... 3. Working with the SoC design team on accelerating the solution using hardware.
Education & Experience
MS/PhD in Electrical Engineering or Computer Science
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