Aiden B.
Machine Learning Engineer @Compass UOL
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WORK HISTORY
Machine Learning Engineer @Compass UOL
San Francisco, CA, US
As an ML/DevOps Engineer, I contributed to the design and implementation of a legal-domain conversational AI platform that uses RAG (Retrieval-Augmented Generation), knowledge graphs, and agentic workflows to deliver natural-language answers grounded in court documents, statutes, and regulatory filings- Designed and automated an end-to-end ingestion pipeline that extracts legal documents from S3, cleans and normalizes text, and loads structured entities/relationships into Neo4j Aura- Implemented AWS Glue jobs to parse unstructured PDFs, identify legal entities (plaintiffs, statutes, citations), and convert them into graph-ready formats (nodes, edges, properties)- Built S3-driven ETL orchestration using AWS Lambda with Step Functions for resilient, event-based data loading.
EDUCATION
University of Southern California
Bachelor's degree, Cognitive Science, Data Science
University of Southern California
Master of Science - MS, Applied Data Science
The American University of Paris
Bachelor's degree
Stanford University
ASES - Entreprenuership Bootcamp
ABOUT AIDEN B.
I am passionate about AI-driven insights and automation, seeking full-time role in Data Science or Data Engineering. I have a Master’s of Science in Applied Data Science and a Bachelor’s in Cognitive Science from USC, with experience in machine learning, big data analytics, neural networks, and scalable data engineering. I’ve worked with teams to develop ETL pipelines, predictive models, and cloud-based solutions at Dell, Boomi, Omatic, and USC Housing. Currently, working on a collaboration project between EverythingALS, Compass UOL, and AWS to develop a Large Language Model (LLM) for diverse structured and unstructured datasets.
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