Back
Mid-level ML role in Bangalore with generalist MLOps skills and legacy brand increases candidate competition.
Healthcare regulatory requirements (FHIR, HIPAA/HITRUST) increase domain specificity though core ML skills remain transferable.
Explicit 3–5 years plus 2 years production ML and mandatory MLOps, cloud, and compliance skills narrow shortlisting strictly.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and maintain MLOps pipelines and CI/CD workflows for ML model deployment in Healthcare Information Systems.
Develop and optimize ETL data pipelines and feature stores integrating healthcare data standards (FHIR, HL7) for model training and inference.
Deploy scalable ML models as APIs/microservices with monitoring for model performance, data drift, and system health, ensuring HIPAA and HITRUST compliance.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or related field.
3–5 years professional experience in software or data engineering; minimum 2 years focused on ML production environments.
Strong proficiency in Python and familiarity with SQL; hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and Docker containerization.
Work location: Bangalore; Hybrid model; Travel up to 10% domestic.
Experience bridging data science and software engineering with strong MLOps and infrastructure skills targeting healthcare use cases.
Familiarity with production ML tooling including MLflow, Airflow, Kubernetes, and healthcare data standards (FHIR, HL7).
Comfortable working in regulated environments with strong focus on security, compliance, and reliable performance of AI services.