Resume

Experience

Founding AI Engineer May 2026 — Present

Hyperspell · San Francisco

I lead work on retrieval and answer synthesis, fusing frontier LLMs with traditional ML to find the right information quickly, get it into the model’s context window, and produce grounded, relevant responses.

Head of AI Apr 2025 — May 2026

HackerPulse · San Francisco

Designed and built the AI service that powers the product — engineering leaders chat with an AI agent connected to live data from GitHub, Jira, Slack, Notion, etc. to get answers about their engineering org
Built a self-reinforcing knowledge graph across all synced integrations — agents discover implicit relationships, each new connection helps surface the next, and the user-facing agent queries it via tool calls

Founding AI Engineer Apr 2023 — Dec 2024

Yuma AI (YC W23) · San Francisco

Fine-tuned Mistral 7B to replace GPT-4 for ticket classification, cutting per-call inference costs by ~100x. Created an LLM-as-judge evaluation system to safely validate prompt changes and migrate between models
Designed an active learning loop for ticket routing: embed tickets → SVM classifies known types → anomaly detector catches out-of-distribution tickets → LLM labels the unknowns → retrain
Implemented the retrieval pipeline combining embedding search with BM25-style keyword matching

Machine Learning Engineer Apr 2019 — Mar 2023

Triplebyte · San Francisco

Joined as the first ML hire; promoted to Tech Lead of Data & Infrastructure
Migrated candidate search from a Postgres read replica (20s on a bad day) to Elasticsearch (60–300ms). Enabled hybrid search: BM25, metadata filters, and vector similarity in one index
Trained a logistic regression to predict which candidates would respond to recruiter outreach — three features, doubled response rate from 20% to 40%
Built a recommendation engine for a two-sided recruiting marketplace using neural collaborative filtering: content-based features handle cold start, collaborative filtering takes over as interaction data accumulates

Data Scientist Oct 2016 — Apr 2018

B23 · McLean, VA

Built an ETL pipeline aggregating millions of points-of-interest from disparate sources for predictive foot-traffic analysis, sold to hedge funds
Automated transfer of hundreds of terabytes of imagery between AWS and Snowball Edge devices for the US Navy, replacing a process that involved burning thousands of DVDs

Software Engineer Jun 2013 — Oct 2016

Agilex / Accenture Federal Services · Chantilly, VA

Developed a semantic search application for matching intelligence reporting with collection requirements via latent semantic indexing, optimizing average query speed by 10x

MS, Data Science Georgetown University · 2016 — 2018

BS, Computer Science & Mathematics Virginia Tech, summa cum laude · 2009 — 2013 Phi Beta Kappa

Python, Ruby, TypeScript, SQL

PyTorch, JAX, NumPyro, OpenAI Agents SDK, LangChain, MCP, LoRA, Hugging Face, scikit-learn, XGBoost, pandas

PostgreSQL, FastAPI, Elasticsearch, Redis, AWS