AI-powered medical documentation platform with legacy EMR integration - BC-1015

Genre de projet: Innovation
Discipline(s) souhaitée(s): Génie -biomédical, Génie, Génie - informatique / électrique, Informatique, Sciences mathématiques
Entreprise: Kadu Care
Durée du projet: 4 à 6 mois
Date souhaitée de début: Dès que possible
Langue exigée: Anglais
Emplacement(s): Vancouver, BC, Canada
Nombre de postes: 1 - 2
Niveau de scolarité désiré: CollègeÉtudes de premier cycle/baccalauréatMaîtrise
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: Yes

Au sujet de l’entreprise: 

Kadu Care is a healthcare technology company incorporated in Canada and Mexico, building an AI-powered medical SaaS platform that automates clinical documentation and streamlines physician workflows. The platform listens to doctor-patient consultations and automatically generates structured clinical notes, including SOAP notes, medical histories, prescriptions, and insurance forms, reducing documentation time by up to 50% and allowing physicians to focus on patient care rather than paperwork.
Beyond note generation, the platform features an AI-powered chatbot that retrieves patient history, answers clinical queries, and supports decision-making in real time. It also includes EHR/EMR integration for centralized patient data management and medical image processing capabilities to extract insights from diagnostic scans in seconds.
Kadu Care serves solo practitioners, private clinics, and large hospital systems through a subscription-based SaaS model, with enterprise licensing available for mid-to-large hospitals.

Veuillez décrire le projet.: 

Kadu Care is developing an AI-powered medical documentation platform designed to seamlessly integrate with legacy Electronic Medical Record (EMR) systems currently in use at major hospital networks in Mexico and North America. The core innovation is the development of automated, intelligent clinical documentation tools that reduce administrative burden on physicians while ensuring compatibility with existing healthcare infrastructure.
The main goal is to build a robust EMR integration layer that connects Kadu Care's AI documentation engine with legacy hospital systems, beginning with one of Mexico's largest hospital networks, while simultaneously supporting evolving feature demands from customers in Canada, the United States, and Mexico.
Main tasks for the the intern include: conducting a technical audit of legacy EMR/EHR architectures and data standards (e.g., HIPAA, FHIR, DICOM) used in target hospital systems; designing and implementing secure API connectors and middleware for bidirectional data exchange; developing and validating AI models for automated SOAP note generation, prescription writing, and medical history summarization from recorded consultations; and iterating on platform features based on direct feedback from clinical users across both markets.
Methodologies and techniques to be applied include: agile software development and FHIR-compliant API design, natural language processing (NLP) and large language model (LLM) fine-tuning for clinical text, medical image processing, cloud infrastructure deployment (AWS/GCP), and user-centered design validated through pilot deployments with physician partners.

Expertise ou compétences exigées: 

Required: Full-stack software engineering (Python, Node.js, React or similar); experience with healthcare data standards and interoperability protocols (HL7 FHIR, REST APIs); knowledge of NLP/LLM integration and fine-tuning for domain-specific applications; cloud infrastructure (AWS or GCP); database design and management (SQL/NoSQL); API development and middleware/integration layer architecture; familiarity with clinical workflows and EHR/EMR systems; UI/UX design skills at a basic to intermediate level, including the ability to prototype and iterate on user interfaces for clinical applications.
Assets (Not necessary): Experience with legacy EMR systems (e.g., Epic, OpenMRS, or proprietary hospital systems); medical informatics or health informatics background; bilingual capability (English/Spanish) for cross-market deployment; experience with DICOM or medical imaging pipelines; prior work in regulated/compliance-sensitive software environments (HIPAA, NOM-024-SSA3 in Mexico); machine learning model deployment and MLOps; advanced UX/UI design for clinical applications including user research and usability testing.