Lead Engineer/Tech Lead for ML Medical Imaging: Hands-on Tech Lead Engineer focused on R&D, ML and DSP

Oncoustics is revolutionizing the use of point of care ultrasound in liver care through advanced AI. We are supported by high-profile institutional investors and have deep partnerships in place with several major ultrasound and pharmaceutical players. We are looking to hire a senior ML Engineer/Scientist to join our team with relevant academic experience and deep industry experience. A successful candidate will be able to manage and lead a team and projects, as well as coordinating with signal processing, clinical data and product teams. The candidate should be able to build on previous work, and have a collaborative team spirit. Specifics of the opportunity include:

Responsibility
• Self-identify issues, form a plan/team with consideration of other constraints, communicate and execute
• Some engineering/project management
• Hands-on coding ~80% of this role is a dev/scientist, 20% as team lead
• Lead all development and deployment of deep learning and machine learning models in tensorflow and pytorch
• Design models/learning strategies to optimize mining of unique ultrasound signal data with deep learning
• Apply custom hyper parameter tuning methods
• Work directly with a team of data scientists and signal processing engineers
• Influence feature engineering and signal processing, and coordinate for optimal mining with AI
• Remain aware of new innovations in the use of AI/ML in medical imaging and ultrasound
• Adopt state of the art algorithms and models for that include multi-instance learning strategies, attention and GANs
• Plan for deployment of all models in Oncoustics future apps
• Participate in FDA planning and clearance of algorithms

Requirements
• Must have tech depth in ml/dsp engineering
• Must have some experience taking ml/dsp from r&d to commercial solution
• Graduate degree in a related field, and relevant undergraduate
• 5+ years at least of industry experience in the development and deployment of AI/ML models for health care
• Expertise in Python for Deep Learning and Machine Learning packages: Pandas, Sklearn, Keras, Tensorflow, Pytorch
• Deep Learning architecture design: Experience with attention mechanisms, multi-instance learning and/or GANs

Good To Have
• PhD/graduate work in comp sci/machine learning/machine vision or related degree
• Expertise in medical imaging analysis or signal processing with AI
• Experience in the use of ultrasound
• Prior experience with FDA clearance of AI/ML algorithms