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Moore Macauley
Intern Backend Developer specializing in AI, multi-agent systems, and computer vision
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Backend-focused Python engineer who built core systems for an AI beauty-advice product: converting facial-recognition landmarks into usable facial measurements and dynamically shaping chatbot context for personalized guidance. Also worked on high-volume data ingestion at AINVESTgroup, improving agent context selection via a RAG database when upstream tags were unreliable, and has strong Git/GitOps + automated testing practices from rapid-deadline delivery environments.
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Key Strengths
- Owned and built major portions of a Python backend integrating facial recognition outputs with an AI chatbot
- Solved facial landmark misalignment by deriving needed points via averaging and validation logic
- Implemented user-in-the-loop measurement correction to improve downstream accuracy
- Prioritized chatbot context using deviation-from-average logic based on a plastic-surgery-style measurement system
- Handled high-volume incoming data relevance issues by using a RAG database to improve context selection
- Applied GitOps-style workflow with short-lived branches and expanding automated test coverage to support rapid iteration
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