Professional Background
Experience
ML systems, data pipelines, model training, evaluation workflows, and analytics experience across contract, industry, and research environments.
Machine Learning Engineer (Contract), Mercor
- Designed Python-based pipelines for LLM-driven task execution, reproducibility, and workflow efficiency.
- Built evaluation frameworks for agent-based ML systems, including benchmarking and failure analysis.
- Analyzed LLM-generated workflow failure modes and improved task reliability in production-like environments.
Machine Learning Engineer Intern, Ericsson
- Designed similarity-based filtering and matching pipelines for high-dimensional signal data.
- Built preprocessing and feature engineering workflows for large-scale WiFi datasets using Python, NumPy, and Pandas.
- Developed and benchmarked ML and deep learning models with PyTorch, TensorFlow, and scikit-learn.
- Created evaluation and visualization tools for model analysis, performance tracking, and technical reporting.
Sales Operations Analyst, China Telecom
- Built SQL-based dashboards to monitor KPIs, sales trends, and operational performance.
- Maintained customer and sales data quality for reporting and downstream analysis.
- Partnered with regional teams to translate operational questions into repeatable data workflows.
Ph.D. Research, University of Regina
- Researched machine learning algorithms for signal-based indoor localization and fingerprint matching.
- Developed methods involving search-space reduction, temporal learning, knowledge distillation, and structured attention.
- Published journal and conference work spanning ML-based localization, 5G simulation, and signal analysis.