About me

I design backend systems, build full-stack web applications, and create developer tools that improve performance and scalability. With internship experience at Google, Meta, and Stripe, I've worked on high-impact services involving GraphQL APIs, real-time monitoring, and low-latency infrastructure. My personal projects range from automated grading platforms to nutrition planning apps and portfolio analytics tools. Driven by clean architecture and user-centric design, I'm seeking full-time software engineering roles where I can contribute to building robust, scalable solutions.

What I'm Doing

  • design icon

    Web Development

    Building responsive websites

  • design icon

    Machine Learning

    Developing AI models

Testimonials

  • John Timberwood

    John Timberwood

    An excellent developer!

  • Bob Smith

    Bob Smith

    Amazing work on our project!

John Timberwood
quote icon

John Timberwood

An excellent developer!

Companies

Resume

Education

  1. Purdue University

    2000 - 2025

    Studying Computer Science.

Experience

  1. Solutions Architect Intern

    May 2024 - Jan 2025

    Saved ∼7 hours per week by developing web scraping automations using Python and Power Automate for the forklift comparison project, integrated Angular widgets into the internal website to enhance functionality Projected annual savings of approximately $500,000 by training machine learning models for OCR and document analysis of Statement of Work (SOW) documents Streamlined marketing ads data retrieval by optimizing API calls and building efficient data pipelines on Palantir Developed a CI/CD pipeline on Azure Cloud for deploying the SOW document analysis application

  2. Software Development Apprentice

    Dec 2024 - Jan 2025

    Deployed a python package to reduce the manual effort of converting Material Safety Data Sheets to cover sheets that can comply with UN GHS Standards Achieved ∼5000 hours/year in time savings (parsing time reduced from 40 mins to 2 mins per data sheet) for Merck Scientists by automating and streamlining data sheet parsing Project involved cross-geographical collaboration with 7 members

  3. ML Research Apprentice

    Dec 2024 - Jan 2025

    The project focused on improving the performance of ML models that produce knowledge graphs on drug-related health records to aid research by health professionals Used BERT transformer model to perform Information Extraction tasks, including Named Entity Recognition and Relation Extraction from a Harvard Medical School dataset focused on Adverse Drug Events Fine-tuned a bioBERT model for Named Entity Recognition using hyper parameter optimization techniques like Hyperband and Population-based training, leading to significant training result improvements of 5%

My skills

Contact

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