🚀 Machine Learning Engineer | Data Scientist I’m a Machine Learning Engineer with a Master’s in Artificial Intelligence from Northeastern University, specializing in Large Language Models (LLMs) and MLOps. I have hands-on experience in building scalable NLP and quantitative models, optimizing ML systems on AWS and Google Cloud, and enhancing model interpretability with interactive dashboards for actionable insights. 💡 Professional Highlights: • Production-Ready AI Pipelines – Led the migration of ML pipelines to AWS SageMaker, automating workflows and improving deployment efficiency. Optimized performance by 8.6% using techniques like SMOTE sampling and data augmentation. • Generative AI & NLP Models – Developed and fine-tuned LLMs and Retrieval-Augmented Generation (RAG) systems for domain-specific tasks, leveraging frameworks like PyTorch, Hugging Face, and LangChain. • MLOps & Scalable Systems – Built CI/CD pipelines with Airflow, MLflow, and Docker, enabling data validation, drift detection, and real-time predictions. • Research-Driven Insights – Delivered data-driven strategies for stakeholders by creating interactive dashboards and conducting feature importance analysis to make ML systems more interpretable.