As a full-stack software developer, you will bring strong system architecture experience and a solid understanding of cloud platform design to provide best-in-class solutions to complex business problems using a modern tech stack.

For millions of people with swallowing disorders, preventing potentially deadly aspiration pneumonia requires following prescribed safe eating strategies. But adherence is poor, and caregivers’ ability to encourage adherence is limited by the onerous and socially aversive need to monitoring another’s eating. We have developed an early prototype for an intelligent assistant that monitors adherence and provides feedback to the patient, and tested monitoring precision with healthy subjects for one strategy called a “chin tuck.” Results indicate that adaptations of current generation machine vision and personal assistant technologies could effectively monitor chin tuck adherence, and suggest the feasibility of a more general assistant that encourages adherence to a wide range of safe eating strategies.