ML Research Engineer

Position Overview As an ML Research Engineer at Circadia Health, you will research, design, and build the next generation of models and algorithms that power our clinical monitoring platform. Circadia's devices use radar to continuously and contactlessly capture respiratory rate, heart rate, and movement data from thousands of patients – alongside audio and other physiological signals. This continuous sensing data is paired with deep clinical context from EHR integrations including conditions, medications, clinical notes, and care events, resulting in a dataset of extraordinary scale and depth that we've only begun to tap. Your work will push into novel problem domains: physiological foundation models, patient activity monitoring, radar-based bed-exit detection, and voice-based phenotyping – turning research ideas into production-grade systems that run on Circadia's devices and cloud infrastructure. Reporting to the Principal ML Engineer, you will work at the intersection of research and engineering: formulating hypotheses, designing experiments, implementing models, and deploying them into real clinical environments. You will collaborate closely with clinical research, signal processing, and data teams to validate algorithms, define data collection requirements, and support regulatory approval. This role requires a strong scientific mindset paired with a deployment-first mentality. We're looking for someone who can rapidly translate research papers into working code, iterate through experiments with rigor, and ship models that perform reliably on real patient data.