Image Processing and Deep Learning Engineer

Summary

Posted: Dec 19, 2024

Role Number:200583128

We are seeking a talented Image Processing Engineer to join our team. The job will focus on developing deep learning solutions for image restoration for new imaging solutions. You will be part of an interdisciplinary team driving Apple’s products.

Description

Deep learning development: Design, implement, and optimize deep learning models for various tasks in the field of Image restoration. Implement and validate models using various data sets. Prepare, filter, process, and analyze large-scale datasets to train and evaluate models. Analyze the results of your algorithm and compare with other leading methods. Optimize models for real-time performance and resource efficiency. Research: Explore how algorithm approaches can mitigate artifacts of new imaging systems. Investigate sensor fusion techniques for these applications Stay updated with recent advancements in the field. Collaboration: Work in sync with interdisciplinary teams of SW, HW and Camera Architecture engineers. Integrate models into larger products or research studies.

Minimum Qualifications

• Strong foundation in image processing computer vision, machine learning, and deep learning.
• Proficiency in Python and deep learning frameworks (e.g. PyTorch).
• Hands on experience with developing real time deep learning solutions, using large scale datasets.
• Experience with optimizing models in both size and runtime
• PhD or Master's degree in Computer Science, Electrical Engineering, in related research fields.
• 3 or more years of relevant experience.

Preferred Qualifications

• Experience with Vision Transformers, Diffusion Restoration models.
• Experience with Geometrical models, Monocular and Stereo Depth Estimation.
• Publications in top-tier computer vision conferences (CVPR, ICCV, ECCV).
• Analytical and detail-oriented with a knack for problem-solving.
• Proficient in both written and verbal communication.
• Ability to work both autonomously and collaboratively.