Resume

Software Engineer

Skycubed • San Diego, California

February 2024 - Present

Developed proprietary software for DoD clients within a mission-critical R&D lab environment, serving as the technical translator between domain experts and engineering teams to convert complex data pipelines and analysis workflows into scalable production systems. Owned the design and implementation of the platform ontology within Palantir's Maven Smart Systems, leading and mentoring the team on ontological data modeling and the downstream AI integration opportunities it unlocks. Designed and deployed full-stack applications and data pipelines that abstracted sophisticated cyber readiness analysis into intuitive interfaces, accelerating the research and analysis cycle for non-engineering stakeholders. Leveraged a modern technology stack including React, Golang, Docker, Python, various Microsoft Azure Government services, Terraform, and GitLab/GitHub CI/CD pipelines. Maintained an active Secret clearance while pursuing Top-Secret clearance. Additionally, took internal initiative to lead and author a technical proposal for a new contract opportunity, conducting independent research literature review to inform model selection and architecture decisions, and designing and prototyping a deep learning pipeline using a Siamese U-Net model with ResNet backbone to automatically detect and score structural damage from satellite imagery. Proposed a high-level system design spanning cloud infrastructure, geospatial visualization, and multi-modal data integration including auxiliary ML models for supplemental data sources.

Lead Software Engineer

Triton Funds LLC • San Diego, California

June 2023 - January 2024

Owned all architecture and implementation decisions end to end for a proprietary financial data pipeline, engineering a solution that automated the identification of investment opportunities and company valuations using LLMs. Collaborated with company leaders and team members throughout the process, leading task distribution, code review, version control, and system architecture decisions. Integrated NLP and AI models, multi-source data APIs, AWS DynamoDB for storage, and LLMs to extract insights from SEC filings at scale. Engineered Python-based web sockets to consume high-volume daily filing streams and automated fund notifications via AWS Lambda.

Data Science Intern

Relay Health • Remote

January 2023 - June 2023

Partnered with company leaders to develop data pipelines and automated data reporting systems, contributing to data analysis and system architecture design and implementation. Delivered an automated reporting pipeline encompassing daily activity reports, optimized user group assignments, and an activity-based segmentation model to identify high-risk users.

Data Science Intern

UniGroup CA • Remote

June 2021 - August 2021

Completed an intensive data science training program working alongside professional data scientists, gaining hands-on experience applying machine learning concepts including linear regression, classification, decision trees, and neural networks using PyTorch to real-world datasets.

Burnstack.ai

Startup cost command center SaaS that centralizes cloud and AI spend (OpenAI, Anthropic, OpenRouter, Supabase, Tavily), with secure multi-tenant workspaces, encrypted provider integrations, automated sync/ingestion pipelines, and invoice-based cost import for reliable burn tracking.

QuantVision.ai

Founded and architected QuantVision.ai, a financial data platform centralizing company filings and financials, designed to scale into a comprehensive analysis solution for emerging and seasoned analysts. Serves terabytes of company filings via AWS S3 and structured financial data via a managed PostgreSQL instance, with infrastructure designed to scale into a production-ready platform. Technology stack included a full Typescript/Next.js frontend and backend with several backend microservices written with Python's FastAPI and Golang, with the main webapp hosted on Vercel and microservices on Google Cloud. Currently developing an agentic AI with LangChain's DeepAgents package that interfaces with a Neo4j knowledge graph containing industry and company relationships and Elasticsearch for full text and vector search to aid in proposal creation and investment theses.

LLMfit.io

A site to aid users looking to see if their hardware will be able to run a specific LLM model locally.

Built binary classifier for brain tumor MRIs in PyTorch using a pretrained ResNet-152 model.

Implemented an empirical comparison of supervised learning algorithms using a machine learning pipeline that automated feature selection, hyperparameter tuning, and model comparison.