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Popular ML engineer role, metro Bangalore location, 3–5 years band, broad MLOps and data skill requirements.
Core MLOps skills transferable but healthcare regulatory and FHIR/HL7 experience increases domain specificity.
Explicit 3–5 years requirement, 2+ years ML production, HIPAA/HITRUST and specific tooling mandates.
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Build and maintain MLOps and CI/CD pipelines for deploying, testing, and versioning ML models in healthcare information systems.
Deploy scalable ML model APIs and microservices ensuring clinical performance and latency requirements.
Develop ETL data pipelines and integrate ML outputs with healthcare applications while ensuring compliance with security standards like HIPAA and HITRUST.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or related field.
3–5 years of professional experience in software or data engineering; minimum 2 years experience with ML production environments.
Strong proficiency in Python and familiarity with SQL; experience with cloud providers (AWS, Azure, or GCP) and containerization tools (Docker).
Work location: Bangalore (Hybrid); Travel: Up to 10% domestic.
Experienced in building and operating MLOps pipelines focusing on reliability, scalability, and data integrity in healthcare.
Hands-on with cloud infrastructure, containers (Docker/Kubernetes), and familiar with ML deployment tools like MLflow and Kubeflow.
Comfortable working in regulated environments adhering to security compliance standards such as HIPAA and HITRUST.