Algorithm Developer - Computer Vision

Company Description

LiteBC is committed to leveraging cutting-edge technology to improve population health. As innovators in the healthcare industry, our mission is to develop advanced solutions that enhance medical diagnostics and patient care. Our flagship product, the HemoScope, is designed to provide immediate and non-invasive blood analysis at the point of care, revolutionizing traditional medical practices.

Role Description

This is a full-time, on-site role for an Algorithm Developer specializing in Computer Vision, located in Yoqneam Illit. The role involves developing and implementing algorithms with a focus on computer vision applications, utilizing advanced techniques in pattern recognition. Responsibilities include collaborating with cross-functional teams, designing and optimizing algorithms, and ensuring their integration with the broader software development process to support the performance of LiteBC's innovative technologies.

Responsibilities

• Design and implement machine learning algorithms for analyzing medical video images captured by our proprietary spectroscopy-based microscope.
• Research and integrate state-of-the-art methods in computer vision and image analysis (both deep and classical methods) to enhance the accuracy and efficiency of ML models.
• Develop and maintain scalable data processing pipelines and model deployment workflows.
• Enable the work of large-scale clinical trial data to support the development and validation of predictive blood count models.
• Collaborate closely with physicists, software engineers and HW engineers in a fast-paced, multidisciplinary environment.

Qualifications

• MSc or PhD in Computer Science, Electrical Engineering or a related field.
• A top performer with at least 5 years of hands-on, post-academic experience in developing deep learning and computer vision algorithms.
• Ability to lead algorithm development from ideation through implementation, including experimental design, iterative development, and performance evaluation.
• Expertise in classical computer vision methods and modern deep learning frameworks such as PyTorch and numerical libraries such as numpy and scikit-learn. 
• Excellent problem-solving skills, critical thinking, and the ability to work both independently and collaboratively in a multidisciplinary team.
• Experience working with medical or biological data is an advantage.