Develop and deploy signal processing algorithms for radar-based contactless monitoring systems. Responsibilities include extracting clinical features from sensor data, validating algorithms using clinical studies, documenting work for regulatory and intellectual property needs, and implementing algorithms on embedded devices. The role collaborates with product, clinical research, data science, electronics, firmware, and algorithms teams to move innovations from research into shipped healthcare products.

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.

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.