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Tier-1 brand, Bangalore metro, and mid-level popular ML role increase competition.
Specialized LLM, MLOps, and real-time ML skills limit cross-industry transferability.
Multiple mandatory ML, MLOps, and LLM productionization skills plus 5+ years requirement.
Build and manage end-to-end lifecycle of predictive models and AI agents to improve payment transactions and reduce failures.
Develop and deploy advanced LLM-driven payment solutions including payment method recommendations, downtime management, and transaction retry.
Collaborate with engineering, compliance, and operations teams to implement AI solutions and stay updated with latest AI/LLM research for practical application.
5+ years of experience in AI/ML engineering or data science roles.
Expertise in Python, Spark, and SQL (Presto/Hive) with strong fundamentals in ML concepts like bagging, boosting, online learning, and recommendation systems.
Hands-on experience with Agentic frameworks such as LangGraph, LangSmith, or LangChain for LLM orchestration.
Experience in productionizing ML solutions using MLOps tools like MLflow, Kubeflow, TFX, or SageMaker; cloud deployment experience required.
Proven ability to independently design, develop, and deploy scalable predictive and generative AI solutions in production environments.
Strong technical skill set combining core ML, generative AI frameworks, and MLOps for real-time and batch workflows with focus on payments domain.
Comfortable working in flat team structures with ownership of complex AI-driven product features impacting financial transactions across multiple countries.