Data-centric AI Engineer specializing in scalable infrastructure for machine learning. Leverages 2 years of experience optimizing real-time ETL pipelines at Goldman Sachs to design scalable AI architectures and automate end-to-end learning lifecycles in production.
Python, GCP (GKE), Terraform, RAG
Architected a multimodal RAG system transforming audiobooks into interactive Q&A; engineered a timestamp-alignment algorithm using FasterWhisper to ground LLM responses in specific audio segments. Implemented a "Spoiler-Safe" reasoning engine using Google Gemini and BGE-m3 embeddings.
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Python, LangChain, OpenAI API, Flask, ReactJS
Developed a context-aware knowledge platform leveraging large language models for information retrieval and conversational learning. Implemented RAG-based querying with structured prompt templates and a full-stack web interface.
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Python, K-Means, PCA, Matplotlib, Scikit-learn
Built K-Means clustering models on a dataset of ~68K ranked players to classify gameplay behavior using metrics such as fighting efficiency, farming, vision control, and objective participation.
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ML, LSTM, BERT, LDA, Flask
Created a real-time sentiment classification system comparing ML models (Logistic Regression, SVM, Random Forest) and deep learning models (LSTM, BERT) using TF-IDF and Word2Vec. Deployed a Flask web app integrated with LDA topic modeling.
View Project23 Marcella, Roxbury
Boston, MA, USA – 02119
+1 (857) 339-8452