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Clairyon is hiring a Senior Full-Stack Software Engineer (Machine Learning) to design, develop, and maintain web applications powering the clinical AI platform. The role focuses on front-end interfaces, back-end services, and production-grade machine-learning integrations, with API development for real-time clinical and sensor data.
You will work with data scientists, clinicians, and product teams to translate research models and workflows into scalable software, while participating in
Clairyon Inc. is a clinical artificial intelligence company focused on transforming acute care and patient monitoring through predictive analytics and agentic AI. Built on research from leading academic institutions, Clairyon offers the CLAIRE Continuum of Care Platform, a comprehensive ecosystem of advanced clinical decision support tools. This includes the COMPOSER predictive model, which has demonstrated significant reductions in sepsis mortality, and robust post-discharge and quality monitoring solutions validated in top medical journals. By combining longitudinal electronic health records with real-time biometric sensor data, the platform enables proactive detection of high-risk conditions, automated care quality monitoring, and improved clinical documentation. Team members collaborate in a mission-driven environment aimed at improving outcomes from the emergency department to the home.
This is a full-time, on-site role based in San Diego, CA for a Senior Full-Stack Software Engineer (Machine Learning). The person in this role will design, develop, and maintain end-to-end web applications that power Clairyon's clinical AI platform, including both front-end user interfaces and back-end services. Daily responsibilities include implementing production-grade machine learning integrations, building APIs to ingest and process real-time clinical and sensor data, and optimizing data pipelines and model serving infrastructure for performance, reliability, and security. The engineer will collaborate closely with data scientists, clinicians, and product teams to translate research models and clinical workflows into scalable, user-centric software solutions. Additional tasks include code reviews, unit and integration testing, documentation, and contributing to architectural decisions and best practices across the engineering organization.