Design, build, and operate scalable, fault-tolerant data pipelines ingesting EHR and device data (ADT, meds, notes, vitals). Transform, validate, and load into MySQL and Snowflake on AWS. Ensure HIPAA/SOC2-compliant handling of PHI, monitoring, incident response, and collaboration with ML, backend, and clinical teams to support analytics and model workflows.

Research, prototype, and deploy ML models for physiological sensing (radar, audio, other signals). Design experiments, implement production-grade models for cloud and on-device inference, optimize for constrained compute, collaborate with clinical and engineering teams, and contribute documentation and regulatory evidence.

Own and operate end-to-end ML infrastructure: build and maintain Airflow pipelines, CI/CD and IaC for model training/deployment, manage MLflow registry, deploy to AWS and edge devices, implement monitoring/data-versioning, ensure HIPAA/SOC2 compliance, and support reproducible, reliable ML in production.