Matthew
Frank's
Virtual Resume.

Machine Learning Enthusiast & Data Scientist

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about me

I am a Machine Learning Engineer with a Master's Degree in Information and Data Science from UC Berkeley. I specialize in modern AI/ML systems including Computer Vision, Natural Language Processing, and Agentic AI architectures. My expertise spans visual recognition, large language models, RAG systems, and multi-agent workflows for real-world applications.

I have extensive experience building production-ready AI systems across multiple domains. My work includes developing Computer Vision systems like celebrity facial recognition achieving 98% accuracy, implementing NLP solutions with Chain-of-Thought reasoning reaching 95% accuracy, and architecting agentic workflows using LangGraph for intelligent automation. I'm passionate about leveraging cutting-edge AI technology—from vision models to LLMs—to solve complex problems across diverse domains.

phone

310-413-2539

Matthew Frank's professional headshot - Machine Learning and Data Science specialist

education

2012 - 2016

Associate of computer science

El Camino College

Torrance, CA

Initially pursuing a major in Chemistry, I discovered my passion for Computer Science at El Camino College. This revelation led to a profound shift in my academic focus and career aspirations. I immersed myself in programming and computational problem-solving, quickly realizing the potential of technology to drive innovation and change.

2016 - 2018

bachelor of computer science

University Of California, Santa Cruz

Santa Cruz, CA

I furthered my studies at the University of California, Santa Cruz, where I earned my Bachelor's degree in Computer Science. My time at UC Santa Cruz was marked by deep dives into software engineering and data structures, which paved the way for my career. I pursued machine learning research, spending the next five years developing innovative solutions and models that leveraged deep learning and predictive analytics to solve complex problems.

2023 - 2024

Masters of Information and Data Science (MIDS)

University of California, Berkeley

Berkeley, CA

I was fortunate to pursue my Master's degree in Information and Data Science at UC Berkeley. My studies have gone beyond traditional data science techniques to include cutting-edge technologies in generative AI and large language models (LLMs). My work focuses on the development and ethical implications of these technologies, preparing me to contribute to and lead in the evolving landscape of AI and machine learning.

skills

Python
Machine Learning
AWS & Google Cloud
Hugging Face
TensorFlow & PyTorch
NLP & LLMs
Agentic AI (LangGraph, RAG)
Computer Vision

experience

  • July 2024 - Present

    Machine Learning Engineer

    Live Data Technologies

    Los Angeles, CA

    At Live Data Technologies, I developed a time-series neural network integrating Transformer, LSTM, and attention mechanisms to predict job tenure with a 10% accuracy improvement. I spearheaded the enrichment of 80 million records using APIs like HERE Maps and OpenAI, standardizing location, education, and industry data to improve downstream model performance. Additionally, I designed and implemented Chat LDT, a LangGraph-powered agentic chatbot leveraging Chain of Thought (COT) reasoning and integrating internal APIs, web search, and Python tools, achieving 95% accuracy in natural language workforce analytics.

    Oct 2023 - Present

    Machine Learning Engineer

  • Sep 2021 - Oct 2023

    Machine Learning Research Manager

    Uniquify, Inc

    San Jose, CA

    Led computer vision R&D in segmentation, facial recognition, pose estimation, and defect detection for semiconductor inspection and multimedia applications. Designed CI/CD pipelines for the Seraphim project, reducing integration times by 30%, and managed a team of engineers to refactor legacy systems into modern Python-based architectures, enhancing performance and maintainability.

  • Oct 2018 - Sep 2021

    Machine Learning Research Engineer

    Uniquify, Inc

    San Jose, CA

    Led computer vision R&D developing state-of-the-art models for facial recognition, pose estimation, segmentation, and defect detection. Built "Bethel" - a celebrity facial recognition system with 10K+ images achieving 98% accuracy. Implemented pose estimation models for human activity recognition and developed segmentation pipelines to enhance object detection. Applied defect detection models to semiconductor manufacturing data, significantly improving early error identification and visual quality assurance.

    Oct 2018 - Sep 2021

    Machine Learning Research Engineer

Projects

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Matthew Frank

ML Engineer & Data Scientist

phone

310-413-2539

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