📫 How to reach me

• chris-github@sunshinelobby.com
• 720 864 1012

👀 I’m interested in Machine Learning / AI / Robotics / Computer Vision

... I have worked in all of these techs

Current focuses @ Vivun

Advanced NLG on Foundation models

• Lead for Prompt Engineering and prompt management
• Technical prompts leveraging model outputs to generate human expressive explanations
• Integration of guardrails-ai
• Prompt analysis through Weights & Biases (wandb.ai)
• RLHF system established through Arize (arize.ai)

NLP for Calendar Event management

• BERT modeling
• Domain rules
• Cosine Similarity
• TF/IDF
• XGBoost

Time series assessment of historical activities

• Segmented Random Forest
• Structured and novel methods for assessing model fitness
• Bayesian data framework (older version)

MLOps development and restructure

• Productized solution for Fargate ECS w/ Step Functions
• Structured process for mass training on Sagemaker Training
• Advanced visualizations using Plotly Dash
• Graduated to visualization and reporting on Weights & Biases (wandb.io)
• Adopted Arize for visualization of production model performance (arize.ai)
• Developing full MLOps solution on Sagemaker & Bedrock utilizing MetaFlow

Previous jobs

• CV -- Scuba Steve
  • Human-assisted rapid annotation
    • Pixellib
    • MaskRCNN on Tensorflow
    • DeepMask / SharpMask on PyTorch
    • Dash web app
  • Identify hands entering equipment during operation
  • Flare operational status
  • Robocar - hobby project to get autonomous car around a track
• Predictive Maintenance
  • Oil pump behavior monitoring and tagging
  • Oil and Gas equipment downtime and PHM
• Robotics
  • minor degree in Controls Theory
  • first eight years of career was micro-robotics ... digital controls theory
• ML @ Seagate
  • Sr. Director of Corporate Division for ML & DS
    • Managed through CRISP-DM
    • Co-developed internal DS University
    • Lead ML over 14 data scientist
  • Sr. Director of Asia-wide team developing AI Failure Analysis of Hard Disk Drives
    • Massive Random Forest project to analyze 3M+ returned drives per quarter
    • Enabled finding true primary issues vs. "most recently returned."
    • Led to a significant reduction in quality control assessment
    • Ultimately reduced FA staff from 600 to 350
  • 90-day report on forecast problems reduced to 3 days

🌱 I’m currently learning

• University of Texas Austin - MSAI - ECD May 2025
  • Reinforcement Learning -- in progress
  • Natural Language Processing -- in progress
• Fourth Brain AI building with LLM - completed May 2023
• Fourth Brain AI program on MLE - completed Oct 2021
  • Regressions
  • Neural Networks
  • Capstone: automated annotation and training with unknown objects in images
• University of Colorado MS in Data Science - stopped to transfer to UT Austin program
  • Courses completed
    • Ethics in DS
    • Basics in HPC
    • Algorithms

Background

• Years overseas running multi-country division

  • Worldwide ownership for Global Failure Analysis Strategic Planning
  • 7 campuses in Thailand, China, Malaysia, Korea, Singapore
  • Two years living in China, two years living in Thailand
  • WW Customer Service ... constant contact with key customers
  • WW Failure Analysis ... leadership for all 12 campuses
  • Massive project using Random Forest
  • Increased visibility to critical problems by 100%+++
    • Reduced staffing from 600 - 350 over three years

• Before that, many leadership roles. Key skills

  • Project management
  • Firmware/software delivery (SCRUM / Agile)
  • Firmware task awareness/development
  • Multi-team collaboration
  • Strategic alignment between divisions

🌱 I have learned

• Torch -- UT Austin NLP
• Tensorflow2 -- Deeplearning.ai
• John's Hopkin's -- Data Science in R
• Stanford DS -- Machine Learning in Octave (Matlab)
• Business Management -- Harvard Business School
• Six Sigma Black Belt
• Problem Solving & Decision Making -- Kepneger-Tregoe
• Telecommunications -- BSEE
• Controls Theory -- sub-degree during BSEE