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Niche MLOps role in Mumbai with mid-level experience draws moderate competition.
Core MLOps skills transfer across industries, but advisory governance emphasis adds domain specificity.
Explicit 3+ years MLOps requirement plus Azure and MLOps tool mandates increase screening rigor.
Deploy, monitor, and optimize AI models and MLOps pipelines on Azure, ensuring performance, drift detection, and availability telemetry.
Manage model lifecycle including upgrades, version control, rollback, and compliant change management with audit, security, and governance.
Collaborate with AI Developers, Product Owners, and Cloud Architects to ensure scalable, reliable, and cost-effective AI solutions for tax, audit, advisory, and client-facing applications.
Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field.
3+ years of hands-on experience in MLOps and/or AIOps, ideally within Azure cloud environment with expertise in Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry.
Experience with Azure DevOps workflows including GitHub Actions for continuous integration and deployment.
Preferred location: Mumbai.
Experienced in engineering enterprise-grade AI systems focusing on operational reliability, observability, and governance in regulated environments.
Comfortable managing end-to-end MLOps lifecycle including telemetry, incident response, performance tuning, and controlled rollouts.
Consulting experience with a bias for action, workflow design for automation and human-in-the-loop AI systems, and advanced model management techniques such as fine-tuning and RLHF.