Role overview
Monogram Health is a leading multispecialty provider of in-home, evidence-based care for the most complex of patients who have multiple chronic conditions. Monogram health takes a comprehensive and personalized approach to a person’s health, treating not only a disease, but all of the chronic conditions that are present - such as diabetes, hypertension, chronic kidney disease, heart failure, depression, COPD, and other metabolic disorders.
Monogram Health employs a robust clinical team, leveraging specialists across multiple disciplines including nephrology, cardiology, endocrinology, pulmonology, behavioral health, and palliative care to diagnose and treat health issues; review and prescribe medication; provide guidance, education, and counselling on a patient’s healthcare options; as well as assist with daily needs such as access to food, eating healthy, transportation, financial assistance, and more. Monogram Health is available 24 hours a day, 7 days a week, and on holidays, to support and treat patients in their home.
Monogram Health’s personalized and innovative treatment model is proven to dramatically improve patient outcomes and quality of life while reducing medical costs across the health care continuum.
What you'll work on
- Architect and maintain enterprise-grade ML infrastructure, including model versioning, automated testing frameworks, containerization strategies, CI/CD pipelines, and comprehensive monitoring systems for model performance, data quality, and drift detection.
- Drive MLOps strategy and standards across the organization. Mentor data scientists and engineers on production best practices, system design, and scalable architecture patterns.
- Own the complete journey from model development through production deployment, including real-time and batch inference systems, A/B testing frameworks, and automated retraining pipelines.
- Collaborate with clinical leaders, product teams, and data scientists to translate complex healthcare requirements into robust, scalable ML solutions. Present technical strategies to executive stakeholders.
- Build fault-tolerant, compliant systems that meet healthcare security and privacy standards. Establish SLAs, incident response protocols, and disaster recovery procedures for mission-critical ML services.
- Evaluate and integrate cutting-edge MLOps tools and practices. Design systems that scale with Monogram's growth while reducing operational overhead and improving model iteration velocity.