Computer Vision/Deep Learning Scientist

iSono Health is developing a platform that combines automated 3D ultrasound technology with cloud computation and artificial intelligence to empower women and their physicians with early detection of breast cancer. Our platform’s automated operation and software expands ultrasound use in point-of-care diagnostics as well as monitoring of breast health at home, walk-in and mobile clinics. Come join us to build an AI platform for accessible and personalized breast cancer screening to empower women with early detection of breast cancer. iSono Health is looking for a computer vision scientist to join as a key member of our small and growing team to develop state-of-the-art deep learning algorithms in computer vision for classification, localization, and segmentation on 3D ultrasound images produced by our novel wearable ultrasound scanner technology. If you are bright, motivated, interested in cutting-edge healthcare technology and want to make an impact on the lives of millions of women around the world, iSono Health is a place for you. What you do? Research and develop deep learning (DL) models in computer vision for lesion detection, segmentation and classification in ultrasound images. Write production quality code to deploy DL models on various compute platforms Develop algorithms and systems for 3D ultrasound image analysis and feature extraction Work with software & firmware engineers to integrate algorithms into a complete product Build tools and framework for efficient image annotation and DL training pipeline Benefits: Competitive salary and generous stock option plan; Medical, dental and vision insurance; Paid parental leave, vacation time and sick time; Opportunities to attend major scientific conferences and publish research papers; Huge company vision to make an impact on global health Awesome office located in South San Francisco with shuttle to BART and Caltrain; Our patented compact ultrasound scanner captures 3D images through automatic scanning of whole breast volume in 1 min. The device connects to a smartphone/tablet/laptop and is controlled by our mobile app. The data is transferred to a secure cloud for image processing and storage. Our machine learning algorithm uses acoustic biomarkers to identify abnormal masses and assist physician with diagnosis and follow up recommendation.