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davidfertube/README.md
Typing SVG

Portfolio


> AI Engineer | Energy Industry | Greater Houston_

AI Engineer with 5 years of experience building production AI/ML systems for the energy industry. I architect agentic RAG systems, predictive ML pipelines, and compliance automation that run in enterprise environments.

class AIEngineer:
    def __init__(self):
        self.focus = [
            "Agentic RAG & Multi-Agent Orchestration",
            "Predictive Maintenance & Anomaly Detection",
            "MLOps & Production ML Systems on Azure"
        ]

    def deploy(self, model) -> Production:
        return model.notebook_to_production()

Ventures

AI-powered knowledge management platform for oil & gas engineers. 7-stage agentic RAG pipeline with human-in-the-loop review, verified citations, and zero hallucinations. Built for corrosion engineers working with ASTM, API, and NACE specifications.

Next.js 16 React 19 TypeScript Claude Sonnet Supabase pgvector Voyage AI Vercel


Experiments

Predictive Agent — LSTM · Scikit-Learn · Plotly · Docker → Code · Demo

Compliance Agent — PydanticAI · DSPy · Mistral · FastAPI → Code · Demo

Anomaly Agent — Isolation Forest · Gradio · Time-Series → Code · Demo

Vision Agent — Qwen2-VL · Transformers · Gradio → Code · Demo


Open Source Contributions

+ LangGraph    → Refactored FunctionMessage patterns, Enhanced fine-tuning docs
+ Pydantic     → Core library contributions
+ AutoGen      → Fixed Azure AI Client streaming stability
+ CrewAI       → URL validation for Azure Gateways
+ Transformers → Documentation improvements

LangGraph Pydantic AutoGen CrewAI


Technical Stack

AI/ML Core: PyTorch · Scikit-Learn · LSTM · Isolation Forest · Time-Series Agents: LangGraph · AutoGen · CrewAI · PydanticAI RAG: pgvector · ChromaDB · Voyage AI · LlamaIndex MLOps: Model Monitoring · Drift Detection · A/B Testing · CI/CD

Infrastructure Cloud: Azure ML · GCP Vertex AI · AWS SageMaker Containers: Docker · Kubernetes (AKS/GKE) IaC: Terraform · GitHub Actions

Data & Pipelines Processing: Python · SQL · PySpark · PostgreSQL Serving: FastAPI · REST APIs · Streaming Pipelines Domain: SCADA/Sensor Data · Feature Engineering


Background

M.S. Artificial Intelligence — University of Colorado Boulder · Expected 2027

5 years building production AI/ML systems

From adaptive learning engines to real-time blockchain fraud detection to industrial predictive maintenance. I take models from notebooks to production.

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  1. portfolio portfolio Public

    AI Engineer Portfolio | davidfernandez.dev

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