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High - Tier-1 brand, mid-level seniority, popular ML/MLOps role, broad skillset increases candidate competition.
Medium - core MLOps skills transfer across industries but healthcare, FHIR, and compliance experience are preferred.
High - explicit 6+ years and mandatory MLOps, Azure ML, Databricks, MLflow, and observability requirements.
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Design, deploy, and maintain scalable production-grade AI/ML platforms focused on Prior Authorization Automation.
Build and manage MLOps pipelines including model lifecycle management, CI/CD, automated retraining, and monitoring for model/data/performance drifts.
Develop AI observability, governance, compliance controls, and support Responsible AI and production AI readiness at enterprise scale.
6+ years of experience in AI/ML Engineering, Data Engineering, or MLOps.
Strong Python programming skills and experience with ML platforms.
Hands-on experience with Azure ML, Databricks, MLflow, and CI/CD for ML.
Experience deploying and operating ML systems at enterprise scale, preferably on Azure cloud.
Experienced AI platform engineer skilled at operationalizing AI solutions at scale with reliability and observability focus.
Familiarity with Prior Authorization domain, healthcare AI, or related fields like Claims, RCM, or EHR is preferred.
Proven ability to implement governance and Responsible AI frameworks within complex enterprise environments.