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Prodigy
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Fine-tuning
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Computer Programming/Coding
Evaluation/RatingPrincipal Software Engineering | Generative AI & NLP Architect. Brings 15+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Prodigy. Education includes Bachelor of Science, University of Massachusetts, Lowell and Bachelor of Science, Plymouth State University. AI-training focus includes data types such as Text and labeling workflows including Fine-tuning.
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Text GenerationOn going projects for various companies on different agent code generations for specific software engineering topics. Typically there is a rigerious grading rubic used for standard areas specific to SWE. Generally I'm pushing for failure points in coding agents, documenting the conversations, answering standarized ruberics with thoughtful explaninations of my reasoning.
ProdigyTextFine-tuningLed the fine-tuning of large language models (LLMs) on clinical datasets to improve accuracy in healthcare NLP tasks. Designed and deployed retrieval-augmented generation (RAG) pipelines using Titan embeddings, OpenSearch, and AWS Bedrock for real-time clinical applications. Delivered structured NLP outputs for downstream healthcare use cases including HCC risking, clinical trial cohorting, and care gap detection. • Built multi-agent, agentic workflows with LangChain to integrate reasoning, orchestration, and tool use into applied NLP systems. • Developed advanced NLP components such as custom spaCy modules, entity alignment, and hallucination detection for consistent outputs. • Fine-tuned domain-specific LLMs (Gemma, Nova, Gemini) on healthcare data to increase clinical accuracy. • Led and executed the rollout of LLM-based clinical NLP pipelines serving millions of medical records in production.
Bachelor of Science, Business Administration
Bachelor of Science, Information Technology - Software Development
Principal AI Engineer
Director of Software Engineering
