Senior AI/ML Engineer

I lead development of an AI-first fundraising and revenue-operations platform with conversational agents for inbound replies, meeting booking, relationship nurturing, and investor communications across email and CRM channels.

I build production Python agent workflows using Pydantic AI and the Claude Agent SDK, including typed tools, structured outputs, state management, and human handoffs. I design Supabase and PostgreSQL data layers and deploy event-driven AWS services with Lambda, API Gateway, queues, and containerized workers.

I also develop BERT-based models and RAG systems using PyTorch, Hugging Face, LangChain, and LlamaIndex. My work includes document intelligence, semantic search, MLOps pipelines, and reusable React, Angular, TypeScript, and Storybook frontend components.

I led development of concurrent data-ingestion services that extracted GraphQL records into Azure SQL. I implemented GitLab CI/CD and automated deployments to Amazon EKS, while using throughput benchmarking and concurrent processing to improve data-pipeline performance.

I built AWS data infrastructure with CloudWatch, Glue, S3, Airflow, Spark, and Snowflake for model training, evaluation, and inference. I developed Python ML services, classification and ranking pipelines, streaming feature pipelines, and FastAPI inference endpoints for sports-content predictions and marketing workflows.

I also created NLP and GenAI workflows for analyzing COBOL source code and DB2 schemas, and built GPU-accelerated real-time video-processing systems using Rust, GStreamer, NVIDIA DeepStream, PyTorch, NVIDIA Jetson, and embedded Linux.

I developed machine learning capabilities for e-commerce platforms, including product classification, catalog enrichment, search relevance, recommendations, and customer-support automation.

I built Python and FastAPI services that exposed inference and data-enrichment workflows to TypeScript, React, and Node.js applications through REST interfaces. I created NLP pipelines for intent classification, entity extraction, query normalization, and answer retrieval.

I implemented RAG and semantic-search workflows, designed SQL and Python data pipelines, containerized ML services with Docker, and integrated automated testing into CI/CD pipelines. I also added logging and operational dashboards to support traceability, performance analysis, and production issue resolution.

I researched and developed image-segmentation and quantification algorithms for 3D and 4D medical-imaging datasets using Python, C++, ITK, VTK, OpenCV, and CNN-based deep learning.

I implemented document-processing pipelines for OCR output, page segmentation, table reconstruction, text normalization, and machine-parseable records. I trained TensorFlow neural networks and SVM classifiers for document, table, and row categorization.

I defined annotation guidelines and evaluation datasets, performed error analysis, refined features and labels with domain reviewers, and exposed research models through lightweight Python services and batch interfaces.

Bachelor's Degree in Computer Science.