Strong foundation in image processing, computer vision, machine learning, and deep learning. Proficiency in Python and deep learning frameworks (e.g. PyTorch). Hands on demonstrated experience with designing real time deep learning solutions, using large scale datasets. Proficiency in Python and deep learning frameworks (e.g. PyTorch). Experience with model evaluation, debugging, experimental analysis, and failure analysis. 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. PhD or Master's degree in Computer Science, Electrical Engineering in related research fields. 5+ or more years of relevant experience. Experience with video restoration, super-resolution, denoising, deblurring, artifact removal, inverse problems or computational imaging. Experience with advanced implementation architectures on GPU, Dedicated HW or Neural engines. Experience with generative priors (diffusion, flow matching) is an advantage. Background in signal processing, physics, computational imaging or inverse problems. Publications in top-tier computer vision conferences (CVPR, ICCV, ECCV, NeurIPS).
