•Design, develop, and maintain ML infrastructure and pipelines (CI/CD for ML models).

•Automate deployment and monitoring of machine learning models in production.

•Implement model versioning, reproducibility, and rollback strategies.

•Collaborate with data scientists to transition prototypes into production-ready services.

•Build observability tools to monitor model performance, drift, and data quality.

•Integrate with cloud platforms (AWS, GCP, or Azure) for scalable ML deployments.

•Ensure security, compliance, and scalability of ML systems.

•Troubleshoot production issues and improve reliability and latency of ML workflows

•Design, develop, and maintain ML infrastructure and pipelines (CI/CD for ML models).

•Automate deployment and monitoring of machine learning models in production.

•Implement model versioning, reproducibility, and rollback strategies.

•Collaborate with data scientists to transition prototypes into production-ready services.

•Build observability tools to monitor model performance, drift, and data quality.

•Integrate with cloud platforms (AWS, GCP, or Azure) for scalable ML deployments.

•Ensure security, compliance, and scalability of ML systems.

•Troubleshoot production issues and improve reliability and latency of ML workflows