I built my career by moving from manual testing to systems engineering to software development, and I now specialize in Software Development Engineer in Test (SDET) work. At each step, I took on roles that required ownership, not just execution. I served as a primary technical point of contact, led verification and validation efforts, translated requirements into testable outcomes, and drove improvements in system reliability. Today, I design automated tests in C#, expand test coverage using structured and AI-assisted approaches, and analyze defects to strengthen system performance. I focus on aligning system behavior with real-world expectations while enabling teams to deliver with confidence.
I bring a strong academic foundation in computer science, mathematics, and artificial intelligence/data science, which shapes how I approach systems. I think in terms of structure, validation, and measurable outcomes, and I communicate technical insights in a way that supports decision-making across teams. I aim to grow into roles that combine technical leadership, system-level thinking, and high-impact problem solving, especially in environments where reliability, safety, and performance matter.
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AI System Reliability & Decision Analysis
Machine learning reliability study evaluating how intelligent systems classify, interpret, and validate complex data through comparative model analysis, diagnostic evaluation, and evidence-backed performance testing.
Repo: https://github.com/TheAzariaReed/technical-projects/tree/main/TechnicalProjects/PokerHandClassification_AIModelReliabilityStudy -
Signal & Sensor Data Visualization Analysis
Data analysis and visualization project using dimensionality reduction and classification techniques to identify patterns, improve data separability, and interpret complex multidimensional sensor-style datasets.
Repo: https://github.com/TheAzariaReed/technical-projects/tree/main/TechnicalProjects/MachineLearning_VisualizationDrivenModelAnalysis -
Predictive System Modeling & Performance Validation
Comparative predictive modeling project analyzing the performance, convergence behavior, and validation accuracy of Support Vector Regression (SVR) and Artificial Neural Network (ANN) systems using quantitative diagnostics and performance evaluation techniques.
Repo: https://github.com/TheAzariaReed/technical-projects/tree/main/TechnicalProjects/AutoMPG_SVR-vs-ANN_ModelValidation
- LinkedIn: www.linkedin.com/in/theazariareed