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Tier-1 brand, mid-level role, and metro Bangalore location increase candidate competition.
Core ML/LLM and MLOps skills are transferable, though fintech domain knowledge moderately matters.
Explicit 5+ years and mandatory LLM, MLOps, and Spark/SQL requirements enforce strict filters.
Build and manage end-to-end AI solutions focused on payment optimization, agent-native operations, and customer-facing conversational AI within the FinTech ecosystem.
Lead the development, deployment, and continuous optimization of predictive models and LLM-driven AI agents in production environments.
Collaborate cross-functionally with engineering, compliance, and operations to integrate AI capabilities into products and ensure scalability and performance.
5+ years of work experience in data science or related roles.
Expert proficiency in Python, Spark, SQL (Presto/Hive), and fundamental ML concepts such as bagging, boosting, online learning, recommendation engines.
Hands-on experience with generative AI frameworks and LLM orchestration tools (e.g., LangGraph, LangSmith, LangChain).
Expertise in MLOps and productionization using tools like MLflow, Kubeflow, SageMaker on cloud platforms; experience with clean coding and modular design.
Experienced individual contributor comfortable leading AI projects end-to-end with strong ownership.
Deep understanding of FinTech domains such as payments, lending, and insurance across Southeast Asian markets preferred (implied by role focus).
Technical ability to balance model performance with operational trade-offs like latency, cost, and scalability in production AI systems.