Applied Machine Learning and AI Engineer

I design, build, and deploy production machine learning and predictive forecasting models using Python, Scikit-learn, and TensorFlow to support municipal operations and public resource allocation. I also architect automated SQL and Python ETL pipelines connected to Azure Synapse Analytics, with emphasis on data integrity, governance, and operational dashboards.

I lead generative AI and prompt-engineering initiatives that integrate LLM capabilities into mission-critical municipal software services. I have deployed Hugging Face transformer models for document classification and summarization, implemented hallucination detection and bias scoring, and led a five-person engineering and analytics team through iterative sprint delivery.

I supported technical operational staff in a classified federal intelligence environment while adhering to DoD and NGA information-security protocols. My responsibilities included user-access administration, system troubleshooting, hardware deployment, and secure infrastructure-node support across high-security facilities.

I collaborated with systems engineers to diagnose operating-system, peripheral, and network-interface issues. I maintained detailed technical documentation and supported compliance-oriented audits and operational processes.

I fine-tuned instruction-based generative AI models and natural-language workflows to automate internal technical-documentation responses and incident triage. I also developed Python analytics scripts and queried enterprise SQL Server metadata to automate operational reporting pipelines.

I designed and prototyped a GAN for synthetic operational-data generation to improve anomaly-detection workflows, reducing false positives by 27%. I evaluated model complexity, inference latency, and hardware-utilization tradeoffs to maintain SLA compliance for enterprise banking services.

I maintained large-scale batch jobs and high-volume ETL processing schedules using Tivoli and CA Workload Automation, ensuring reliable data processing and data integrity for predictive-modeling feeds.

I developed diagnostic scripts and automated reporting utilities using DFSORT and IDCAMS, reducing batch-processing failures and downtime by 15%. I also assisted engineering teams with migration of legacy on-premise transactional records to cloud-based distributed NoSQL and relational repositories.

In progress. Relevant coursework includes Information Retrieval, Advanced Analytics, Applied Analytics and Methods, Visualization and Dissemination, and Ethical and Evidence-Based Decision Making.

Relevant coursework includes Enterprise Application Development, Database Analysis and Design, Data Mining, Object-Oriented Programming, and Principles of Data Analysis.