Computer Vision Researcher-Video Restoration

24 hours ago


Herzliya, Tel Aviv, Israel Apple Full time $120,000 - $180,000 per year

We are seeking a talented Image Processing Engineer to join our team. The job will focus on developing deep learning solutions for image restoration in new imaging systems. 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.

Preferred Qualifications

Experience with Vision Transformers, Diffusion Restoration models.

Experience with advanced implementation architectures on GPU, Dedicated HW or Neural engines.

Experience with inverse problems

Background in physics

Publications in top-tier computer vision conferences (CVPR, ICCV, ECCV).

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.

PhD or Master's degree in Computer Science, Electrical Engineering, in related research fields.

Proficient in both written and verbal communication.

Ability to work both autonomously and collaboratively.

3 or more years of relevant experience.","internalDetails":null,"eeoContent":null



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