Senior AI/ML Engineer

Designed and deployed enterprise Generative AI platforms using LLMs, RAG architectures, and agentic workflows for knowledge retrieval, document intelligence, and business process automation. Built production AI agents with LangChain and LangGraph for multi-step reasoning, tool integrations, and enterprise workflow automation.

Developed scalable retrieval systems using vector databases, embeddings, semantic search, and hybrid retrieval. Implemented evaluation, observability, and monitoring pipelines, optimized LLM inference with vLLM and GPU acceleration, and designed AWS-based cloud-native infrastructure with Kubernetes, Docker, FastAPI, and MLflow.

Developed machine learning and predictive analytics solutions for forecasting, customer intelligence, and decision-support applications. Built advanced time-series forecasting models using transformer-based architectures and statistical learning techniques.

Designed feature engineering, model training, validation, backtesting, and deployment workflows using Python, SQL, Airflow, AWS, and Docker. Also developed early LLM-powered analytics and embedding-based semantic retrieval systems and collaborated with engineering teams to productionize machine learning services.

Developed machine learning solutions for customer segmentation, behavioral analytics, recommendation systems, and conversion prediction. Built recommendation engines and classification models using TensorFlow, PyTorch, and traditional machine learning algorithms.

Designed NLP, semantic search, intelligent search, classification, and retrieval systems using transformer models and embeddings. Developed scalable data and feature engineering pipelines and deployed containerized ML services with Docker, Kubernetes, FastAPI, AWS, and CI/CD pipelines.

Conducted research and development in machine learning, predictive analytics, anomaly detection, and forecasting methodologies. Developed experimental AI systems for predictive modeling, uncertainty estimation, intelligent decision support, and simulation-based forecasting and optimization.

Applied statistical analysis, feature engineering, and deep learning techniques to large-scale structured datasets using Python, PyTorch, TensorFlow, SQL, Spark, and Hadoop. Collaborated with engineering teams to transition research prototypes into production-ready AI and analytics platforms.

Bachelor's degree in Computer Science.