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AI/ML Engineer with 4+ years of experience designing and deploying scalable machine learning, deep learning, and generative AI solutions in cloud-based enterprise environments. Skilled in building end-to-end AI systems across data engineering, model development, and production-grade deployment workflows. Strong expertise in predictive modeling, large language model applications, and MLOps. Focused on delivering reliable, scalable, high-performance AI-driven solutions for real-time data systems.…AI/ML Engineer with 4+ years of experience designing and deploying scalable machine learning, deep learning, and generative AI solutions in cloud-based enterprise environments. Skilled in building end-to-end AI systems across data engineering, model development, and production-grade deployment workflows. Strong expertise in predictive modeling, large language model applications, and MLOps. Focused on delivering reliable, scalable, high-performance AI-driven solutions for real-time data systems.

Varun Jose Madanu

AI Engineer, Data Scientist, Data Engineer, +3

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AI/ML Engineer with 4+ years of experience designing and deploying scalable machine learning, deep learning, and generative AI solutions in cloud-based enterprise environments. Skilled in building end-to-end AI systems across data engineering, model development, and production-grade deployment workflows. Strong expertise in predictive modeling, large language model applications, and MLOps. Focused on delivering reliable, scalable, high-performance AI-driven solutions for real-time data systems.…AI/ML Engineer with 4+ years of experience designing and deploying scalable machine learning, deep learning, and generative AI solutions in cloud-based enterprise environments. Skilled in building end-to-end AI systems across data engineering, model development, and production-grade deployment workflows. Strong expertise in predictive modeling, large language model applications, and MLOps. Focused on delivering reliable, scalable, high-performance AI-driven solutions for real-time data systems.

Available to hire

AI/ML Engineer with 4+ years of experience designing and deploying scalable machine learning, deep learning, and generative AI solutions in cloud-based enterprise environments. Skilled in building end-to-end AI systems across data engineering, model development, and production-grade deployment workflows.

Strong expertise in predictive modeling, large language model applications, and MLOps. Focused on delivering reliable, scalable, high-performance AI-driven solutions for real-time data systems.

Skills

Experience Level

Expert

Expert

Expert

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Expert

Expert

Expert

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Expert

Expert

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Expert

Expert

Expert

Intermediate

Intermediate

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Beginner

Work Experience

AI/ML Engineer at Fiserv

September 1, 2024 - Present

Contributed to an AI-powered graph intelligence platform for Fiserv's digital payments ecosystem using GraphSAGE, GATv2, and entity resolution to detect payment fraud and mule networks, improving fraud detection accuracy by 29%. Developed scalable fraud detection models using Temporal Graph Networks and heterogeneous graph embeddings for real-time identification of account takeover, payment laundering, card fraud, and anomalous transaction behaviors. Architected AWS-native streaming graph pipelines with Amazon MSK, Kinesis, Lambda, Glue, S3, EMR, Neptune Analytics, and Redshift for real-time ingestion, entity resolution, and graph generation, reducing investigation latency by 31%. Built agentic AI fraud investigation workflows using LangGraph, LangChain, MCP, and RAG for autonomous evidence collection, graph reasoning, semantic risk analysis, and explainable fraud decisions, improving investigator productivity by 34%. Fine-tuned Llama 3.1 and Mistral 7B using QLoRA/LoRA/DPO and Bayesia

ML Engineer at S&P Global India Pvt. Ltd.

May 1, 2021 - July 1, 2023

Developed large-scale anomaly detection and financial risk intelligence systems using real-time market data, pricing feeds, trading events, and customer activity logs, improving incident detection speed by 28% while strengthening security and data reliability. Designed scalable ETL pipelines using Apache Spark, Kafka, Airflow, and SQL to process millions of financial records daily across market data, credit ratings, pricing datasets, and economic indicators for enterprise analytics and reporting. Built and optimized ML models including XGBoost, LightGBM, and Autoencoders for credit risk prediction, market anomaly detection, and pricing validation, improving predictive accuracy by 32% across production systems. Applied BERT and TF-IDF Logistic Regression on financial news and operational documents to identify recurring market trends and improve classification, search relevance, and prioritization by 42%. Containerized ML services with Docker and deployed on Kubernetes-based infrastructu