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Circadia Health is a growth-stage healthcare AI company focused on preventing avoidable hospitalizations and transforming senior-care operations. The company has developed the Circadia Intelligence Platform, which combines contactless sensing technology that monitors respiration and motion with medical-grade accuracy, native predictive models that detect 85% of preventable adverse events several days in advance, and enterprise integrations that operationalize predictions directly within EHR, care-coordination, billing, and compliance workflows.
The platform currently touches 40,000+ post-acute patients daily across skilled-nursing, home-health, and home-care networks. The company is backed by leading healthcare and AI investors and is headquartered in El Segundo, CA.
As a Senior ML Ops Engineer, you will be responsible for building and maintaining the infrastructure, pipelines, and systems that enable machine learning models to run reliably in production at scale. This role bridges machine learning research and production operations, ensuring models are deployed efficiently, monitored continuously, and optimized for performance and cost.
Key responsibilities include designing and implementing ML deployment pipelines, managing model versioning and experiment tracking, setting up monitoring and alerting for model performance and data quality, optimizing inference infrastructure for latency and throughput, collaborating with data scientists and backend engineers to operationalize models, and ensuring compliance with healthcare regulations and data privacy requirements.
You will work with modern ML infrastructure tools and cloud platforms, contribute to architectural decisions around model serving and data pipelines, and help establish best practices for ML operations across the organization. The role offers the opportunity to impact healthcare delivery at scale while working with cutting-edge AI and healthcare technology.
