Designing and deploying Generative AI systems using GPT-4, BERT, and LangChain for summarization, content generation, and conversational intelligence.

Implementing Retrieval-Augmented Generation (RAG) with FAISS, Pinecone, and pgvector for high-precision semantic retrieval.

Deploying large models on AWS SageMaker and Google Vertex AI, integrating continuous evaluation and drift monitoring via MLflow.

Building modular, containerized FastAPI microservices for AI inference using Docker and Kubernetes

Developed NLP pipelines for sentiment analysis and compliance report summarization using GPT-3, BERT, and T5.

Built semantic and vector-based search systems with FAISS and Pinecone for financial document intelligence.

Automated MLOps workflows using Airflow, Docker, and SageMaker for scalable retraining and CI/CD deployment.

Applied SHAP and LIME for explainable AI and integrated Grafana dashboards for production monitoring.

Developed scalable machine learning pipelines in Python and PySpark for churn prediction and risk analytics.

Built NLP systems using spaCy, Word2Vec, and TF-IDF for sentiment and intent classification.

Deployed APIs with Flask and Docker, orchestrated using Kubernetes for distributed inference.

Introduced MLflow-based model tracking and experiment versioning to streamline MLOps workflows.