Experience

The work, in order.

A timeline of the roles, research, and programs that took me from self-taught code to machine learning engineering — most recent first.

Work experience.

Machine learning at Apple and Lawrence Livermore, software engineering at Linean, research and teaching at CSU Bakersfield.

  1. May 2026 – Aug 2026 Incoming
    Walt Disney Company

    Machine Learning Engineer

    Walt Disney Company · Bakersfield, CA

    • Incoming Summer 2026 on Disney's Ad Platform Team!
    Ad Platform
  2. Oct 2025 – Present
    Linean

    Software Engineer

    Linean · Bakersfield, CA

    • Developed a Grant Management System (GMS) for the California Commission on Teacher Credentialing to support administration of over $10 million in state educator stipend funding using ASP.NET.
    • Designed and developed Linean.com, increasing traffic by 800%.
    ASP.NET
  3. May 2025 – Aug 2025
    Apple

    Machine Learning Engineer Intern

    Apple · Austin, TX

    • Interned with the Artificial Intelligence & Data Platforms (AiDP) team within Apple's IS&T organization.
    • Reduced search time by 60% for Apple's Slack users by developing and deploying a production-grade semantic search and summarization bot using FastAPI, OpenSearch, Apple's Foundation Models, and Kubernetes.
    • Automated Snowflake sandbox view creation, reducing request fulfillment time from ~2 days to minutes, by building a secure Streamlit platform with role-based access, Apple Auth, and Snowflake API integration.
    • Developed and deployed two RESTful APIs integrated with SAP test systems, now powering a Slack-based LLM workflow.
    • Designed a proof-of-concept anomaly detection engine across 18,000+ time-series supply chain datasets using LSTM Autoencoders and Isolation Forests, paired with a GenAI Streamlit interface for SQL exploration and anomaly analysis.
    FastAPI OpenSearch Kubernetes Foundation Models Streamlit Snowflake REST APIs LSTM Autoencoders Isolation Forests
  4. Aug 2024 – Dec 2024
    California State University, Bakersfield

    Machine Learning Research Assistant

    CSU Bakersfield · Bakersfield, CA

    • Develop ML models with University Faculty to predict influenza contraction likelihood based on environmental factors.
    • Achieved 60% lower MAE and 80% fewer parameters using a GRU/CNN hybrid model than prior research.
    • Conducted initial data preprocessing and feature engineering to optimize the hybrid model's performance.
    GRU CNN Feature engineering
  5. Jul 2024 – Aug 2024
    Lawrence Livermore National Laboratory

    Data Scientist Intern

    Lawrence Livermore National Laboratory · Livermore, CA

    • Applied advanced machine learning techniques (CNNs, RNNs, DNNs) using PyTorch, TensorFlow, and scikit-learn to reconstruct electro-anatomical maps and classify arrhythmias from 12-lead ECG data.
    • Achieved 98% accuracy through four deep learning models, increasing sensitivity in detecting arrhythmias.
    • Integrated ML workflows, to implement a GRAD-CAM, enhancing model interpretability for domain scientists.
    PyTorch TensorFlow scikit-learn CNNs RNNs Grad-CAM
  6. Jan 2024 – Present
    California State University, Bakersfield

    Web Development Coordinator

    California State University Bakersfield · Bakersfield, CA

    • Led a team that designed and developed the Career Pathways, California Energy Research Center, AI Hub & Math Dept websites.
    • Increased traffic by 27% average across all sites.
    Leadership Web development
  7. Jan 2024 – May 2024
    California State University, Bakersfield

    Advanced Web Development Teaching Assistant

    CSU Bakersfield · Bakersfield, CA

    • Mentored 25+ Students in debugging backend systems and designing REST APIs for server-side web applications.
    • Provided academic support to students needing help with Node.JS, PHP, Shell, JS, and HTML/CSS.
    • Facilitated a 5–10% increase in average student grades compared to previous course iterations.
    Node.js PHP Shell JavaScript HTML/CSS REST APIs

Projects & programs.

Selective programs and the work I built inside them.

  1. 2023
    Stanford University

    Stanford Deep Learning Portal Projects

    Stanford University

    • One of fourteen students out of 120 nationwide who participated in an intensive machine-learning program at Stanford.
    • Implemented a neural style transfer model to generate artistic images.
    • Created object detection models, classification models, and more, while collaborating with Ph.D. researchers.
    Python TensorFlow Keras Jupyter Matplotlib
  2. Externship
    Beats by Dre

    Beats By Dre Sentiment Analysis

    Beats by Dre

    • Comprehensive sentiment analysis on consumer reviews as part of the Beats By Dre Externship.
    • Web scraping (Oxylabs, BeautifulSoup), EDA, and advanced NLP (Gemini AI API) to interpret customer feedback.
    Python TextBlob BeautifulSoup Pandas Matplotlib NumPy
  3. Jul 2024
    Capital One

    Capital One Launchpad Participant

    Capital One

    • One of 50 students nationwide selected for a HACU-partnered program.
    • Built a Python credit-profitability calculator.
    • Won 1st place out of 100+ participants.
    Python Finance modeling

Education.

  1. Summer 2026 Expected
    California State University, Bakersfield

    California State University Bakersfield

    Bachelor of Science in Computer Science · Minor in Applied Statistics · Bakersfield, CA

    • GPA 3.70.
    • Dean's List: Fall 2023, Spring 2024.
    • Helen Hawk Honors Program.
    • CSUB Hispanic Scholarship Fund Recipient.
    • SHPE Scholar.

    Certifications

    • Convolutional Neural Networks
    • Neural Networks
    • Hyperparameter Tuning
    • Data Visualization with Matplotlib and Seaborn
    • AWS Cloud Foundations
    • AWS Machine Learning Associate (in progress)

    Relevant courses

    • Programming I–II
    • Discrete Math
    • Advanced Web Development
    • Calculus I–II
    • Computer Architecture
    • Statistics
    • Applied Statistical Computing
    • Physics I
    • Convolutional Neural Networks
    • AWS Cloud Foundations

Technical skills.

Languages

  • C++
  • Python
  • JavaScript
  • PHP
  • Java
  • SQL
  • NoSQL
  • Shell
  • R
  • TypeScript
  • React
  • Node
  • C#

AI & ML

  • PyTorch
  • TensorFlow
  • Keras
  • NLP
  • LLMs

Web & APIs

  • Flask
  • FastAPI
  • REST APIs
  • Streamlit
  • Slack Bolt
  • WebSockets
  • HTML
  • CSS/SCSS
  • jQuery

Data

  • Pandas
  • NumPy
  • Jupyter
  • Tableau
  • Snowflake
  • Matplotlib
  • Seaborn
  • BeautifulSoup
  • TextBlob

DevOps & cloud

  • Git
  • GitHub
  • CI/CD
  • Linux
  • macOS
  • Windows
  • AWS EC2
  • AWS S3
  • AWS Elastic Beanstalk
  • AWS Bedrock
  • AWS SageMaker
  • AWS Kinesis
  • Docker
  • Kubernetes

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