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Tier-1 brand, mid-level AI role in Bangalore with broad ML/LLM/MLOps requirements increases competition.
Strong ML/LLM production skills transfer across industries, but fintech domain knowledge raises sensitivity.
Explicit 5+ years plus mandatory ML, LLM, MLOps, and cloud productionization requirements.
Build and manage critical AI and data science models for financial services including payment optimization and automated operations.
Develop and deploy advanced Generative AI and LLM-based solutions, owning the end-to-end lifecycle from development to production and optimization.
Collaborate with engineering, compliance, and operations teams to integrate AI capabilities into products and continuously incorporate latest AI research into practical applications.
5+ years of experience in data science or AI roles as an individual contributor.
Expert proficiency in Python, Spark, SQL (Presto/Hive), and core machine learning concepts such as Bagging, Boosting, and Recommendation Engines.
Hands-on experience with Agentic frameworks (LangGraph, LangSmith, or LangChain) and LLM orchestration for Generative AI development.
Experience in productionizing ML solutions using MLOps tools like MLflow, Kubeflow, SageMaker and deploying scalable components on cloud platforms.
Experienced in financial services domain AI applications including payments, insurance claims automation, and customer-facing conversational AI.
Strong engineering discipline with clean coding, modular design, and version control practices aligned with scalable production ML.
Capable of independently leading AI solution delivery from concept to deployment in a relatively flat team structure with cross-functional collaboration.