Featured on YouTube
I publish hands‑on walkthroughs and research explainers. These are four of the most relevant for hiring managers.
AI Breakthrough Democratizes Open-Source LLMs! Introducing QLoRA and the Guanaco Family (opens on YouTube in a new tab)
Open Source LLMs Score Again! Introducing MPT-7B, Commercially Usable and Free of Charge (opens on YouTube in a new tab)
Install Stable Diffusion Locally: Quick Setup Guide with Ubuntu 22.04 (opens on YouTube in a new tab)
How to Fine-Tune Open-Source LLMs Locally Using QLoRA! (opens on YouTube in a new tab)
Selected Projects
AI Forecasting System for Interconnected Business Data
Deep learning with Graph Neural Networks (GNNs) to model cross-entity relationships (products, people, regions, devices) and forecast context‑aware outcomes.
ForecastingGraphsGNNE2E
Real systems are interdependent. Modeling the graph directly yields better demand, risk, and capacity forecasts.
- Nutrition/CPG → ingredients ↔ suppliers ↔ plants → demand & supply risk
- Car rentals → branches ↔ hubs ↔ customer flow → vehicle availability
- Retail → products ↔ co‑purchases ↔ categories → SKU‑level demand
Estimating Outcomes from Sequences + Static Data
Neural architecture that merges time‑ordered events with item attributes to predict numeric outcomes as a live service.
PredictionSequencesTabularMLOps
Combines what happened (sequence) with what it is (attributes) for high‑accuracy predictions.
- Logistics → time‑to‑depletion from movement history + item specs
- E‑commerce → AOV/abandonment from user sessions + product/customer features
LLM Customization & Edge Deployment
Fine‑tune compact LLMs and deploy offline on consumer GPUs/embedded devices with full training→eval→inference pipeline.
LLMEdgeFine‑tuningLatency
Low‑latency, privacy‑preserving inference without third‑party APIs.
- Support intent routing
- In‑store voice assistant
- Developer command tools
Human Activity Recognition with Pose Estimation
MoveNet + temporal CNN/LSTM to classify actions in real time on commodity hardware.
VisionPoseEdgeSafety
Gesture, safety, and task‑stage recognition without wearables.
- Warehouse ergonomics
- Queue behavior
- Gesture UI
Private Document Chat (Local RAG)
Fully local retrieval‑augmented generation with private embeddings and vector search—no data leaves the environment.
RAGPrivacyLLM
Regulatory‑friendly Q&A over sensitive docs.
- Legal case files
- Clinical protocols
- Finance audit trails
Bulk Document → Structured Data
OCR + rules + NLP to turn PDFs/Word/scans into clean spreadsheets at scale.
AutomationOCRETL
Searchable datasets and QA over previously opaque documents.
- Retail reports
- Grocery invoices
- Field notes
Predictive Modeling on Structured Data
End‑to‑end pipeline from cleaning and features to interpretable models and production hooks.
TabularXGBoostShapProd
Actionable churn/returns/LTV predictions wired to dashboards and ops.
- Marketing churn
- Returns risk
- Purchase likelihood
Time‑Series Forecasting
Neural & classical models for seasonality, events, and anomalies across any logged metric.
ForecastingAnomalyARIMADeep
Anticipate demand, detect shifts, improve planning.
- DAUs
- Energy use
- Store traffic
Computer Vision for Operations
Train detectors/classifiers for shelves, packaging, safety, and custom inspections.
VisionDetectionRealtime
Automate visual checks and reduce manual review.
- Stock levels
- Planogram QA
- PPE compliance
Automated AI QA for Manual Workflows
Find duplicates, conflicts, and missing fields across human‑entered data before it ships.
QAAutomationData Quality
Protect quality and margin while reducing tedious checks.
- Catalogs
- Briefs
- Specs
About & CV
Methodical, analytical, and hands‑on data scientist with eight years in AI. I ship forecasting, returns reduction, LTV/churn prediction, and private LLM tooling. Prior projects include distributed training of clinical LLMs on AWS, reproduction of peer‑reviewed models, and production vision systems. I like clean data paths, clear metrics, and fast feedback loops.
TensorFlowPyTorchXGBoostscikit‑learnPythonSQLAWSGCPAzureDockerKubernetesNLPComputer VisionTime‑SeriesGraphs (GNN)
Experience
Machine Learning Engineer — Artisight
Remote · Jun 2022 – Present
- Delivered ML/DL and vision services for hospitals; improved predictive automation reliability.
- Spun up 8‑GPU AWS cluster for distributed LLM pretraining on hundreds of millions of clinical notes.
- Reproduced peer‑reviewed outcomes models (mortality/LOS/readmission) with AUCs ~0.945/0.881/0.889.
Data Scientist — KPMG
New York, NY · May 2021 – Jun 2022
- Built NLP pipelines (regex, Transformers, DNNs, XGBoost) for contract extraction at >0.95 precision/recall.
- Predicted client turnover; collaborated across 20+ stakeholders to productionize models.
Machine Learning Engineer — Resource Capital Funds
Denver, CO · May 2020 – May 2021
- Automated ~10% of investment decisions via 6 ML models + GUI on AWS EC2; metals exploration targeting.
- Led small team of consultants; deployed live analytics tooling for decision support.
Business Analyst Intern — Spectrum
Centennial, CO · May 2019 – Aug 2019
- Performed statistical analysis (PCA, MCA, Odds Ratios, Chi‑Squared, regularized logistic regression).
- Presented findings to leadership; ~5% cost savings.
Data Scientist Intern — Arrow Electronics
Centennial, CO · May 2018 – Aug 2018
- Built SQL pipelines (Oracle/MySQL) and dashboards (Tableau/QlikView) to support marketing campaigns (≈8% sales lift).
- Shipped internal web apps for market intelligence and e‑commerce.
Education
B.S. in Computer Science (Minor in Math)
University of Northern Colorado — Monfort College of Business
Magna Cum Laude, GPA 3.85/4, Beta Gamma Sigma (top 8%) — Founder: AI Club & IoT Club
May 2020
Certifications
- Azure AI Engineer (AI‑102) — Feb 2022
- Azure Fundamentals (AZ‑900) — Jan 2022
- TensorFlow Developer Specialization — Jan 2021
- AI Foundations for Everyone (IBM) — Dec 2019
- Machine Learning (Andrew Ng) — Jan 2019
Open to roles in ML Engineering, Data Science, and Applied Research.
Let’s talk