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Metro Mumbai, mid-level 3+ years, and popular MLops role yield moderate candidate competition despite Azure specialization.
Core MLOps skills are transferable but enterprise Azure governance and domain controls add moderate specificity.
Explicit 3+ years MLOps/AIOps and Azure tool requirements create strict technical screening.
Deploy, monitor, and manage AI models on Azure, ensuring performance, drift detection, availability, and governance controls.
Develop and maintain MLOps pipelines using Azure ML and GitHub Actions for continuous integration, deployment, and lifecycle management of AI solutions.
Optimize AI inference infrastructure for performance and cost efficiency, implement compliant change management, and collaborate across teams for enterprise-grade AI deployments in tax, audit, advisory, and client-facing applications.
Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field.
3+ years of experience in MLOps and/or AIOps with hands-on experience in Azure cloud services including Azure ML, Synapse, Data Lake, App Services, Cosmos DB.
Experience with AI model deployment, monitoring, version control, and cost/performance optimization on Azure.
Preferred location: Mumbai. Work Experience Required: 3+ years in relevant field.
Experience working in consulting environments with a bias for action, able to handle structured rollout and governance of AI systems.
Familiarity with Azure DevOps ecosystem, including App Insights, Log Analytics, Key Vault, Managed Identity integrations, and tools for inference performance testing.
Strong understanding of model observability, telemetry, incident response, and AI workflow design including prompt flow and human-in-the-loop systems.