Real-time clinical AI for health systems
Bayesian Health builds a real-time clinical intelligence platform that analyzes patient records to detect risks like sepsis and deterioration, surfacing actionable insights to clinicians within EHR workflows. It serves health systems to enable proactive care, reducing mortality, readmissions, and length of stay. Proven in peer-reviewed studies with high adoption and measurable outcomes.
Builds and maintains scalable AWS infrastructure, CI/CD pipelines with GitHub, and secure AI Ops platform for clinical AI/ML products. Requires 5+ years in DevOps/SRE, Kubernetes proficiency, Terraform expertise, and healthcare compliance experience.
Builds and deploys scalable full-stack clinical AI/ML products, integrating with healthcare workflows and enterprise systems. Requires 3+ years full-stack experience with React/TypeScript, cloud platforms like AWS, relational DBs, and AI coding tools.
Leads AI/ML organization by setting technical vision, building and mentoring data scientists/ML engineers, architecting scalable ML infrastructure, and hands-on prototyping models for healthcare applications. Requires PhD, 8+ years shipping ML products, and 3+ years leading ML teams.
Leads technical integrations of clinical AI platform with client EHR systems, develops automation tooling for implementations, and collaborates cross-functionally. Requires 5+ years forward deployed experience and full stack skills in React/TypeScript and cloud/databases.
Builds analytics infrastructure, frameworks, and tools for monitoring clinical AI/ML product performance, enabling clinical case reviews, and driving cross-functional insights. Requires 5+ years experience with Python, SQL, cloud data platforms, and handling sensitive health data.
Leads clinical health system accounts through implementation, adoption, and expansion using data-driven strategies. Requires clinical background (nurse/therapist) and 5+ years in client success/account management to drive renewals and outcomes.
Develops, productionizes, and deploys end-to-end ML models for real-time clinical predictions using production Python/SQL. Owns model performance from prototyping to real-world impact, collaborating cross-functionally. Requires PhD + 3+ years shipping ML products.
Owns end-to-end ML lifecycle from prototyping clinical prediction models to productionizing and deploying them using production-grade Python/SQL. Requires PhD +3yrs or Master's +5yrs experience with MLOps tools like SageMaker/MLFlow.
Leads revenue growth by developing sales strategies, managing accounts in hospital systems, and building relationships with C-level executives to drive adoption of AI healthcare solutions. Requires 7+ years in healthcare/SaaS sales, team leadership, and data-driven decision making.