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Hi, I’m Lalithendranath G, an AI/ML Engineer with 3+ years of experience delivering end-to-end ML and DL solutions across Banking, Telecom, Healthcare, E-commerce, and Retail. I specialize in Generative AI with hands-on experience in LLMs (GPT-3/4, BERT, T5, LLaMA) and toolchains like HuggingFace, LangChain, and RAG-based automation. I’ve built scalable AI-powered systems, optimized for fraud detection, real-time underwriting, churn prediction, clinical NLP, intelligent assistants, and adaptive pricing, and I’m proficient in NLP pipelines, model development, evaluation, and deployment using cloud platforms. I enjoy turning complex data into actionable insights, leading cross-functional teams, and delivering reliable MLOps pipelines with MLflow, Airflow, Kubeflow, Docker, Kubernetes, and monitoring with Prometheus and Grafana. My experience spans Big Data processing with Spark, Kafka, Databricks, and cloud-native deployments on AWS, Azure, and GCP. I’m passionate about building AI that augments decision-making, small teams, and enterprise-scale adoption.…Hi, I’m Lalithendranath G, an AI/ML Engineer with 3+ years of experience delivering end-to-end ML and DL solutions across Banking, Telecom, Healthcare, E-commerce, and Retail. I specialize in Generative AI with hands-on experience in LLMs (GPT-3/4, BERT, T5, LLaMA) and toolchains like HuggingFace, LangChain, and RAG-based automation. I’ve built scalable AI-powered systems, optimized for fraud detection, real-time underwriting, churn prediction, clinical NLP, intelligent assistants, and adaptive pricing, and I’m proficient in NLP pipelines, model development, evaluation, and deployment using cloud platforms. I enjoy turning complex data into actionable insights, leading cross-functional teams, and delivering reliable MLOps pipelines with MLflow, Airflow, Kubeflow, Docker, Kubernetes, and monitoring with Prometheus and Grafana. My experience spans Big Data processing with Spark, Kafka, Databricks, and cloud-native deployments on AWS, Azure, and GCP. I’m passionate about building AI that augments decision-making, small teams, and enterprise-scale adoption.

Lalithendranath G

Data Scientist, AI Engineer, AI Developer, +2

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Hi, I’m Lalithendranath G, an AI/ML Engineer with 3+ years of experience delivering end-to-end ML and DL solutions across Banking, Telecom, Healthcare, E-commerce, and Retail. I specialize in Generative AI with hands-on experience in LLMs (GPT-3/4, BERT, T5, LLaMA) and toolchains like HuggingFace, LangChain, and RAG-based automation. I’ve built scalable AI-powered systems, optimized for fraud detection, real-time underwriting, churn prediction, clinical NLP, intelligent assistants, and adaptive pricing, and I’m proficient in NLP pipelines, model development, evaluation, and deployment using cloud platforms. I enjoy turning complex data into actionable insights, leading cross-functional teams, and delivering reliable MLOps pipelines with MLflow, Airflow, Kubeflow, Docker, Kubernetes, and monitoring with Prometheus and Grafana. My experience spans Big Data processing with Spark, Kafka, Databricks, and cloud-native deployments on AWS, Azure, and GCP. I’m passionate about building AI that augments decision-making, small teams, and enterprise-scale adoption.…Hi, I’m Lalithendranath G, an AI/ML Engineer with 3+ years of experience delivering end-to-end ML and DL solutions across Banking, Telecom, Healthcare, E-commerce, and Retail. I specialize in Generative AI with hands-on experience in LLMs (GPT-3/4, BERT, T5, LLaMA) and toolchains like HuggingFace, LangChain, and RAG-based automation. I’ve built scalable AI-powered systems, optimized for fraud detection, real-time underwriting, churn prediction, clinical NLP, intelligent assistants, and adaptive pricing, and I’m proficient in NLP pipelines, model development, evaluation, and deployment using cloud platforms. I enjoy turning complex data into actionable insights, leading cross-functional teams, and delivering reliable MLOps pipelines with MLflow, Airflow, Kubeflow, Docker, Kubernetes, and monitoring with Prometheus and Grafana. My experience spans Big Data processing with Spark, Kafka, Databricks, and cloud-native deployments on AWS, Azure, and GCP. I’m passionate about building AI that augments decision-making, small teams, and enterprise-scale adoption.

Available to hire

Hi, I’m Lalithendranath G, an AI/ML Engineer with 3+ years of experience delivering end-to-end ML and DL solutions across Banking, Telecom, Healthcare, E-commerce, and Retail. I specialize in Generative AI with hands-on experience in LLMs (GPT-3/4, BERT, T5, LLaMA) and toolchains like HuggingFace, LangChain, and RAG-based automation. I’ve built scalable AI-powered systems, optimized for fraud detection, real-time underwriting, churn prediction, clinical NLP, intelligent assistants, and adaptive pricing, and I’m proficient in NLP pipelines, model development, evaluation, and deployment using cloud platforms.

I enjoy turning complex data into actionable insights, leading cross-functional teams, and delivering reliable MLOps pipelines with MLflow, Airflow, Kubeflow, Docker, Kubernetes, and monitoring with Prometheus and Grafana. My experience spans Big Data processing with Spark, Kafka, Databricks, and cloud-native deployments on AWS, Azure, and GCP. I’m passionate about building AI that augments decision-making, small teams, and enterprise-scale adoption.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Gen AI/LLM Engineer at Epic Systems

August 1, 2024 - Present

Designed and led the development of an AI-driven real-time insurance underwriting and adaptive pricing system, enabling personalized risk assessment and improved operational efficiency. Applied models such as XGBoost, LightGBM, and LSTM for predicting claim frequency and customer behavior, plus time-series forecasting. Used CNNs for image-based claim submissions to automate damage detection and speed up claim resolution. Implemented end-to-end ML workflows with Kubeflow, Vertex Pipelines, and Airflow; exposed services via FastAPI/Flask microservices; deployed on Google Vertex AI and integrated with vector databases (FAISS, Pinecone, Weaviate) for RAG-enabled underwriting. Fine-tuned LLMs (LLaMA, Falcon, Mistral) against domain tasks using Gemini/Claude APIs. Led Kubernetes/Docker/Spark-based real-time inference and built semantic graphs with Neo4j/AWS Neptune for enhanced search and reasoning.

ML Engineer at ZenQ

January 1, 2022 - July 1, 2023

Led NLP initiatives for sentiment analysis and topic modeling of customer feedback, delivering actionable product insights. Built a dynamic percentile scoring system with Tableau dashboards for real-time monitoring of recurring customer service incidents. Designed ML models for demand forecasting and inventory optimization (Random Forest, GBM), integrated multiple data sources to create a 360-degree customer view, and enabled targeted promotions. Implemented real-time data streaming with Apache Kafka, containerized models with Docker, and used Hadoop/PySpark on AWS for large-scale analyses. Explored Generative AI with GANs for synthetic data, applied clustering and graph-based methods for fraud detection, and deployed analytics on Google BigQuery and Azure ML for scalable model management.