PpAt Cosmo, we are at the forefront of revolutionizing healthcare through our groundbreaking technology. With our innovative advancements in live endoscopy, we are transforming the landscape of medical diagnostics. We leverage AI to empower physicians, enabling them to make well-informed decisions and significantly improve the lives of their patients. Our dedication to excellence has resulted in creating GI Genius: our AI-enabled medical device for live endoscopy has received FDA approval and is successfully deployed in hospitals worldwide, making a significant impact in the field of healthcare. Check out our website for more information at /p pAs a Computer Vision AI Scientist at Cosmo MedTech AI, you will design, implement, train and validate advanced deep learning models for video-based colonoscopy, contributing to AI products already deployed in hospitals worldwide. In this role, you will collaborate closely with other AI scientists and with data, software, and hardware teams to push the boundaries of the current state of the art and develop AI solutions that enhance real-time clinical performance and improve patient care. If you are passionate about artificial intelligence, computer vision, and healthcare, and want to see your work make a real impact in clinical practice globally, this is the perfect opportunity for you. The level of seniority for this position will be evaluated during the interview process, based on the candidate’s experience and expertise. /p h3Key Responsibilities /h3 ul liActively collaborate with other AI scientists and cross-functional teams to develop and implement AI solutions for medical endoscopy. /li liResearch, implement, train and evaluate advanced computer vision and deep learning approaches for endoscopy video analysis. /li liDesign rigorous experimental protocols and benchmark approaches efficiently on large-scale video datasets. /li liReport findings clearly and effectively through internal reports, presentations, and technical documentation. /li liStay up to date with the latest advancements in computer vision, deep learning, and medical image analysis, and support the team’s continuous learning and scientific publications in top-tier conferences and journals. /li liSupport the integration of developed AI models into existing medical devices and systems. /li liContribute to internal code quality through code reviews and reproducible research practices. /li /ul h3Required Skills /h3 ul liMaster’s degree in Computer Science, Engineering, Physics, Math or related; PhD strongly preferred (CV/ML/Medical Imaging). /li li5+ years of hands‑on experience in deep learning and computer vision (industry or academia); at least part of it on detection/segmentation, tracking and classification problems. /li liStrong proficiency in Python and PyTorch; good software engineering practices (Github/Gitlab). /li liProven track record of working on innovative computer vision projects resulting in scientific publications, patents or public repositories. /li liExcellent analytical, problem‑solving, and communication skills, with a collaborative mindset and the ability to work effectively both independently and as part of a team. /li liFluency in English (written and spoken) /li /ul h3Nice to Have /h3 ul liPrevious work on medical image analysis or endoscopy. /li liPublications or substantial contributions to projects accepted at top computer vision or medical imaging venues (e.g., CVPR, ICCV, MICCAI). /li liExperience with transformer‑based architectures for image and video understanding (object detection, segmentation, tracking and classification), /li liExperience with self‑supervised learning and large‑scale distributed training. /li liExperience with depth estimation, surface reconstruction, or 3D geometry understanding from monocular video. /li /ul h3Physical Requirements /h3 pExpected travel is 30% /p h3Equal Opportunity Statement /h3 pWe support equal opportunities, without any discrimination; The research complies with Legislative Decree 198/2006 /p h3Seniority level /h3 ul liMid‑Senior level /li /ul h3Employment type /h3 ul liFull‑time /li /ul h3Job function /h3 ul liInformation Technology and Science /li /ul h3Industries /h3 ul liSoftware Development and Medical Equipment Manufacturing /li /ul /p #J-18808-Ljbffr