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Tier-1 brand, mid-level ML role, and Bangalore location create high applicant competition.
GenAI, cloud and engineering skills are transferable across industries but require ML-specific experience, so moderate sensitivity.
Explicit 2–6 year band plus mandatory GenAI, Python, Pyspark, Azure, and vector DB skills makes filters strict.
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Design and develop scalable Generative AI applications for software automation and intelligent data retrieval.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines using large language and vision models to enhance chatbot capabilities.
Deploy AI solutions on Azure cloud and integrate Python backend services with cloud-native tools for deployment and monitoring.
2 to 6 years of work experience in relevant field.
Hands-on experience with LLMs (GPT, LLama), VLMs, and RAG architecture.
Strong proficiency in Python with frameworks like FastAPI and LangChain, and skills in Pyspark for big data processing.
Experience deploying and managing applications on Azure, including Azure Functions, App Services, and Azure AI services.
Experienced working with Generative AI technologies and RAG pipeline development for production environments.
Able to collaborate across teams to deploy and optimize AI-based cloud solutions on Azure.
Strong software engineering foundation including CI/CD, version control (Git), and cloud-native backend integration.