Deep Learning Engineer

A pioneering Israeli MedTech & AI scale-up engineering real-time Deep Learning and Computer Vision diagnostic solutions to revolutionize clinical endoscopy and medical imaging workflows globally.

Backed by a strategic commercial partnership with one of the world's largest multinational medical device corporations, the company combines commercial stability and international clinical deployment with life-saving algorithmic innovation.

The company's platform operates in real time during live endoscopic procedures, delivering high-precision computer-aided detection and lesion characterization to significantly elevate diagnostic accuracy and patient outcomes.

The R&D group upholds rigorous academic standards, tackling complex real-time video processing, semantic segmentation, and deep learning challenges on massive clinical datasets.

Located in Haifa directly adjacent to primary train transit, operating on an in-office model with flexibility for 1–2 days working from home.

Role Description

• Serving as a Senior Deep Learning & Computer Vision Researcher, joining an elite, close-knit algorithmic core team of five researchers driving real-time medical imaging intelligence.
• Researching, designing, and implementing cutting-edge Deep Learning and Computer Vision algorithms for low-latency, real-time medical image analysis and video stream processing.
• Training, fine-tuning, and optimizing deep neural networks for semantic segmentation, object detection, and feature classification under demanding clinical real-time constraints.
• Applying advanced classical and modern Image Processing techniques to preprocess, normalize, and enhance complex biomedical video data.
• Conducting end-to-end algorithmic R&D: from mathematical modeling and proof-of-concept experimentation to deployment-ready architectures in production environments.
• Collaborating cross-functionally with software architects, embedded systems engineers, and clinical specialists to validate algorithmic accuracy against ground-truth clinical data.

Requirements

• M.Sc. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field – Mandatory
• Demonstrated academic excellence with a GPA of 85+ (or equivalent honors) across all academic degrees – Mandatory
• At least 4 years of proven hands-on experience in Deep Learning applied to Computer Vision / Image Processing – Mandatory
• Strong, practical mastery in designing and training modern vision architectures (e.g., CNNs, Vision Transformers, Semantic Segmentation models) – Mandatory
• Extensive, production-grade hands-on experience developing and training models in PyTorch – Mandatory
• Solid technical proficiency in classical Image Processing algorithms and libraries (e.g., OpenCV) – Mandatory
• Advanced programming capabilities in Python within native Linux environments – Mandatory
• Strong mathematical foundation, analytical rigor, and fluent professional communication in English (written and verbal) – Mandatory