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Tier-1 brand, mid-level AI title, metro location, and generalist ML/LLM requirements increase candidate density.
Strong ML/LLM and MLOps skills transferable, but payments/fintech domain knowledge raises specificity.
Explicit 5+ years and mandatory ML, LLM, and MLOps expertise impose high filtering.
Own end-to-end development, deployment, and optimization of predictive ML models and AI agents to improve payments transaction success and user experience across Southeast Asia.
Build and manage advanced AI solutions leveraging Generative AI and LLM orchestration frameworks within the payments domain.
Collaborate with cross-functional teams including engineering, compliance, and operations to design AI-driven product improvements and operational solutions.
5+ years of relevant work experience in data science or AI engineering roles.
Expert proficiency in Python, Spark, SQL (Presto/Hive) and fundamental ML concepts like Bagging, Boosting, Online Learning, Recommendation Engines.
Hands-on experience with generative AI agent frameworks such as LangGraph, LangSmith, or LangChain and LLM orchestration.
Expertise in productionizing ML solutions using MLOps tools (e.g., MLflow, Kubeflow, TFX, SageMaker) and deploying scalable cloud components.
Experienced in building ML/AI solutions in complex, real-time payments domains across multiple countries or markets.
Demonstrated ability to independently manage full ML lifecycle from research, model development to production deployment and continuous improvement.
Strong engineering discipline with clean coding, modular design, version control and balancing model accuracy with business trade-offs like latency and cost.