THOMAS WOOD

CANDIDATE-ID: TW-773914

OCCUPATIONS: AI SCIENTIST // FARMER // ROBOTICIST

HOBBIES: POLITICAL ECONOMICS // WRITING // MATHEMATICS

LOCATION: LIVE OAK, FLORIDA

SPECIAL ABILITY: AUTOMATION FORCE MULTIPLIER

EXECUTIVE SUMMARY

  • Subject demonstrates exceptional capabilities in applied mathematics and artificial intelligence research
  • Academic foundation in physics and applied mathematics enables advanced problem-solving across multiple domains
  • Current focus: Standardization of internal medicine documentation through AI integration
  • Notable side project: Dexterous manipulation for agricultural automation
  • Assessment: High-value asset for complex scientific and technical initiatives

    • OPERATIONAL HISTORY

    [JAN 2024 - PRESENT]

    APPLIED AI SCIENTIST // PIECES TECHNOLOGIES

    • Prompt engineering for clinical summaries and decision support pipelines
    • Data engineering for LLM pipelines with Airflow, Kubernetes, and Elasticsearch
    • Programming evangelism to physicians with Jupyter notebooks and Streamlit web apps
    • Received commendations for user-friendly prompt testing interfaces
    • Streamlined clinical workflow adoption through interactive notebooks
    [APR 2022 - DEC 2023]

    MACHINE LEARNING ENGINEER // OPTX

    • Architect and deploy advanced data/ML pipeline infrastructure
    • Implement Kubernetes-based ML service deployment architecture
    • Optimize cost efficiency of ML computational resources
    • Design and deploy GPT4 + RAG systems for structured data interaction
    [FEB 2021 - APR 2022]

    ARTIFICIAL INTELLIGENCE RESEARCHER // LIFEBIO

    • Engineered data pipelines for ML development processes
    • Implemented document analysis systems with Hugging Face Transformers
    • Constructed ML service architecture using Docker/Kubernetes on Azure
    • Advanced Speech-to-Text methodologies with SpeechBrain framework
    • Executed distributed training protocols with DeepSpeed
    • Directed ML skill advancement program for technical personnel
    [JUN 2013 - PRESENT]

    LEAD SCIENTIST // SYNPON LABS

    • Question-answering systems development: Theano, PyTorch
    • Humanoid robotics control systems: MuJoCo, Unity, Drake
    • Deep reinforcement learning: TensorFlow, PyTorch
    • Multi-modal computer vision research: PyTorch, Caffe, MS COCO
    • Open source development and technical consultation
    [PRIOR ASSIGNMENTS]
    • PORTLAND GENERAL ELECTRIC [JUL 2020 - DEC 2020]: ML product deployment, cloud architecture
    • NIKE [MAY 2019 - JUN 2020]: ETL systems, analytics visualization
    • HUAWEI [JUL 2018 - JAN 2019]: Visual relation detection, graph deep learning
    • ASTOUND [DEC 2017 - MAR 2018]: AutoML systems development
    • INTEL [MAY 2017 - AUG 2017]: Automated ETL systems
    • MICROSOFT [JAN 2016 - FEB 2016]: Text analysis, AzureML
    • SPORTSWEAR INC [DEC 2014 - MAY 2015]: CUDA/C++ engineering
    • UW MEDICINE [2011 - 2013]: Computational biology research

    ACADEMIC CREDENTIALS

    [GRADUATE STUDIES]

    UNIVERSITY OF WASHINGTON

    DEGREE: M.S. APPLIED MATHEMATICS

    FOCUS: DATA SCIENCE, SCIENTIFIC COMPUTING, ROBOTICS

    [UNDERGRADUATE STUDIES]

    LAMAR UNIVERSITY

    DEGREE: B.S. PHYSICS

    FOCUS: QUANTUM FIELD THEORY, LONGITUDINAL OPTICS

    TECHNICAL SYSTEMS

    • 10+ Years Production Python Architecture & Development
    • High Performance Computing & Systems Optimization
    • Full Stack Development & Cloud Infrastructure
    • Enterprise Linux/Unix Administration
    • Modern DevOps & CI/CD Implementation
    • Distributed Systems & Container Orchestration
    • Scientific Computing & Applied Mathematics
    • Large-Scale Data Pipeline Architecture

    CONTACT PROTOCOLS