DevOps (Machine Learning Operations) (HCM)

- Manage infrastructure across on-premise clusters and AWS cloud, ensuring high availability and scalability.- End-to-End MLOps Pipeline: Own the ML lifecycle from data ingestion, model training, and validation, to deployment and monitoring, using the latest MLOps practices. Also design, impelemnt and maintain feature store pipeline.- Develop and maintain Infrastructure as Code (IaC) using Terraform for provisioning cloud and on-prem resources.- Databricks & ML Deployment: Architect and deploy large-scale machine learning models on Databricks, ensuring high availability, fault tolerance, and compliance with enterprise-grade security standards.- Deploy and manage containerized ML services CI/CD using Kubernetes, with GitOps practices via ArgoCD for ML Platform across Cloud and OnPrem.- Chatbot RAG & LangChain Expertise: design, deployment, and optimization of Retrieval- Augmented Generation pipelines leveraging LangChain to build scalable, performant AI applications.- Network understanding for configure VPCs, subnets, security groups, VPNs, and firewalls in AWS and on-prem environments.- Monitor system performance, troubleshoot issues, and implement improvements for reliability and efficiency.