Software engineering, applied machine learning, and reliable systems.
From infrastructure automation to evaluating how language models behave.
01 / EXPERIENCE
Work history
Lowe’s Companies, Inc.JAN 2026 — PRESENT
Software Engineer — ML
Charlotte, NC · Building reproducible data science workflows and production-ready machine learning solutions.
- Translate business problems into measurable objectives, sampling strategies, and model evaluation criteria.
- Curate labeled behavioral, text, and catalog datasets with ground-truth and label-quality standards.
- Evaluate ML models and LLMs across in-house training, fine-tuning, and external APIs, comparing accuracy, coverage, failure modes, and cost.
- Partner with engineering teams on reproducible testing, data-drift monitoring, and automated retraining triggers.
Rochester Institute of TechnologyJAN 2025 — DEC 2025
AUG 2022 — DEC 2022
Teaching Assistant
Rochester, NY · Hands-on instruction in Python, Bash, Linux, and automation.
- Mentored 150+ students through laboratory instruction in scripting, file processing, and command-line programming.
- Conducted weekly labs, code reviews, debugging, and grading for 1,000+ programming assignments.
- Developed exercises in Linux command-line operations, file handling, and cron automation.
Saunders College of BusinessJAN 2023 — MAY 2024
System Administrator
Rochester, NY · Infrastructure automation, deployment workflows, and enterprise monitoring.
- Migrated applications from Docker to Kubernetes, improving deployment efficiency by 40%.
- Standardized automated provisioning for 200+ systems using Ivanti imaging and deployment tools.
- Implemented Zabbix monitoring across 500+ systems, reducing infrastructure downtime by 25%.
- Resolved 2,000+ application and infrastructure issues with a 95% on-time resolution rate.
02 / TOOLKIT
Skills & tools
Programming & engineering
PythonJavaJavaScriptSQLBashPHPOOPData Structures & AlgorithmsSDLCDebuggingGit
Data science & AI / ML
Machine LearningStatistical ModelingLLM EvaluationPyTorchTensorFlowKerasscikit-learnPandasNumPyRTableauMatplotlibSeaborn
Data engineering & databases
Apache SparkDatabricksKafkaMySQLMongoDBNeo4j
Cloud & systems
AWSDockerKubernetesCI/CDInfrastructure AutomationLinux / UnixWindows ServerActive DirectoryVMwareZabbix
03 / FOUNDATIONS
Education
ROCHESTER, NY · GPA 3.6Master of Science in Data Science
Rochester Institute of Technology
ROCHESTER, NY · GPA 3.6Bachelor of Science in Computing and Information Technologies
Rochester Institute of Technology
04 / EXPLORATION
Projects & research
AI ResearchJAN 2025 — DEC 2025
Bias Characterization in AI-Generated Travel Narratives
Studied cultural and representational bias in LLM-generated travel narratives across models and languages.
- Built a five-layer Python pipeline processing approximately 600,000 online travel comments.
- Evaluated 100,000+ relevant samples across LLaMA 3.2, Gemma 2, GPT-2, and Sarvam.
- Combined human annotations, Detoxify metrics, correlation and distributional analysis, and Bland–Altman testing to identify gaps between human and automated toxicity assessments.
AI ResearchAUG 2025 — DEC 2025
Evolutionary Search for Toxicity Control in LLMs
Developed an evolutionary search framework for iterative response refinement.
- Integrated Perspective API, HateBERT, and embedding-based metrics to evaluate 5,000+ generated responses.
- Designed SentenceTransformers-based semantic toxicity scoring with 92% scoring consistency.
- Achieved a 37% reduction in mean toxicity scores across experimental generations.
Machine LearningAUG 2024 — DEC 2024
Fraudulent Job Posting Classification
Built a predictive model to identify fraudulent opportunities in online job markets.
- Processed 10,000+ job postings with text preprocessing, feature extraction, and five-fold cross-validation.
- Compared Logistic Regression, Random Forest, and Gradient Descent; achieved a 72% F1-score, 80% precision, and 67% recall.
Software EngineeringJAN 2024 — MAY 2024
Tutor Scheduling Application
Led an RIT senior capstone with GCCIS to automate tutor hour tracking.
- Reduced administrative workload by 50%.
- Built Node.js APIs for scheduling, session tracking, and authentication with role-based access control and audit logging.
- Optimized SQL queries and stored procedures to support real-time synchronization.
Systems & ObservabilityAUG 2023 — DEC 2023
Application Performance Monitoring Tool
Developed a lightweight APM solution for Linux systems.
- Created interactive Python dashboards for real-time process metrics and log analysis.
- Proactively detected anomalies and optimized systems, reducing downtime and performance degradation by over 30%.