Generative AI & Software Engineer with 5+ years building production ML systems and scalable data infrastructure. Currently specializing in LLM integration and agentic architectures - recently automated document processing for 1000s of T-Mobile contracts using vision models. Background includes fine-tuning transformers, multimodal document understanding, and time-series neural networks (LSTM). Speaker at Austin Python Meetup and distributed training workshops.

Distributed ML Infrastructure

Building "Embodied OS" - a semantic AI system that analyzes biomarker data (HRV, cortisol, inflammation markers) from fitness assessments and translates physiological stress patterns into personalized wellness venue recommendations. Using bem.ai for contextual analysis and Google Maps API for location intelligence, the app explains why specific venues (restorative yoga for high cortisol, contrast therapy for inflammation) address detected stressors. Exploring the intersection of quantified self-