I combine 10+ years of software quality engineering with an M.S. in Data Science, AI & Machine Learning to build and evaluate AI systems across data pipelines, agents, prompt governance, telemetry, regression testing, and safety.
M.S. Data Science, AI & ML — Boston University
Massachusetts · open to US remote roles
years in software quality, automation, release, and reliability engineering
reviewed AI evaluation cases in the WPH evaluation platform
backend tests passing at a completed WPH stabilization milestone
I designed and built a full-stack AI and data platform combining controlled research agents, source-backed publishing data, prompt governance, execution telemetry, AI evaluation, deterministic safety, and human review.
The model is not the source of truth. WPH separates structured data, evidence, model output, deterministic safety, prompt versions, telemetry, evaluation, and human review so behavior can be reproduced and investigated.
WPH is the flagship above. These projects show the modeling and quality-engineering foundation behind how I build AI systems.
I compared a Random Forest against a linear baseline, then focused on residual behavior and production limits rather than only headline accuracy.
Outcome: residuals exposed systematic error on high-end homes, so I documented that limitation instead of presenting R² alone.
Release testing, automation, APIs, CI/CD, failure analysis, and evidence-based triage shaped how I now design AI evaluations, regression gates, and observability.
See the engineering record →I spent more than a decade asking what happens when software is wrong. I now apply the same discipline to AI systems: what evidence supports the answer, what changes between prompt versions, how do we detect regressions, and what happens when confidence is low?
My M.S. in Data Science, AI, and Machine Learning added the modeling and analytics layer. WPH became the place where I combined both backgrounds into one production-oriented system.
M.S. Data Science, AI & ML — Boston University
10+ years software quality engineering and automation
agents · evals · prompt governance · telemetry · source grounding
Python · SQL · PostgreSQL · analytics · ML validation
I'm interested in full-time US remote roles across Applied AI, AI Evaluation, AI Platform, and advanced data/ML quality.