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Metro location and mid‑level ML/AI role increase applicant competition, though role is specialized.
Role demands specialized ML/AI and Azure skills that are transferable but require focused AI experience.
Explicit 6–7 years plus mandatory LLM, MLops and Azure AI Foundry expertise tightly narrows candidates.
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Lead development and deployment of scalable Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) AI systems and ML Ops pipelines.
Design and automate end-to-end AI workflows using Azure AI Foundry’s Control Plane, prompt flow, and agent capabilities.
Responsible for production-grade AI system lifecycle including model selection, prompt design, evaluation, deployment, monitoring, and ensuring agent reliability.
6 to 7 years of professional experience in AI/ML engineering or related fields.
Expertise with Python programming and FastAPI, ML Ops tools such as MLflow, DVC, CI/CD pipelines.
Experience with Azure AI Foundry including Control Plane, Agent Service, AKS, ADF, and observability tools.
Location requirement: Mumbai (Airoli & Santacruz).
Proven ability to lead development of complex AI/ML systems at scale, especially with LLM and RAG architectures.
Strong hands-on experience in machine learning lifecycle management and automation in Azure cloud environment.
Experience working in enterprise or product environments that demand production-grade AI system deployment and observability.