Responsibilities
Research, design, and implement state-of-the-art deep learning models in computer vision (e.g., detection, segmentation, transformers, self-supervised learning).
Translate research into production-ready algorithms, writing clean, efficient, and scalable code in Pytorch.
Explore creative ideas, experiment with novel architectures, and continuously push beyond current SOTA.
Take ownership of your work end-to-end, from concept through prototyping to deployment in production.
Requirements:
M.Sc. in Computer Science / Electrical Engineering from a leading university. Ph.d – Advantage.
3+ years of hands-on experience in deep learning and computer vision in Python.
Proven ability to train and deploy neural networks with high performance and efficiency.
Full-time availability at our Tel Aviv HQ.
Advantages:
Proven track record of writing and publishing papers in top-tier deep learning or computer vision conferences or journals.
Experience with classical Computer Vision algorithms (e.g. homography, PnP, feature matching).
Experience developing optimized, real-time code for edge devices.
