What I Build

MLOps & Production Infrastructure

RAG Pipeline Deployment

  • Production-ready retrieval systems with vector databases
  • Optimization for latency, cost, and accuracy
  • Monitoring and observability for RAG systems
  • Integration with LLM serving infrastructure

Databricks ML Workflows

  • End-to-end ML pipelines at scale
  • Feature engineering and model training orchestration
  • Model serving and deployment automation
  • Cost optimization and performance tuning

Production Model Serving

  • Real-time inference infrastructure
  • Batch prediction systems
  • A/B testing and canary deployments
  • Auto-scaling and load balancing

Linux-Native Infrastructure

  • Container orchestration (Docker, Kubernetes)
  • Infrastructure as code (Terraform)
  • CI/CD pipelines for ML systems
  • Security hardening and compliance

Technical Stack

Cloud & Infrastructure

  • AWS: Solutions Architect Professional, Advanced Networking Specialist
  • GCP: Professional Cloud Architect, ML Engineer track
  • Azure: AI Engineer Associate
  • Infrastructure: Terraform, Kubernetes, Docker
  • Linux: Native deployment, optimization, security

ML & Data Engineering

  • Databricks: ML workflows, Delta Lake, Unity Catalog
  • Vector Databases: Pinecone, Weaviate, Milvus
  • ML Frameworks: PyTorch, TensorFlow, Spark ML
  • Data Processing: Spark, Kafka, Airflow
  • RAG Systems: LangChain, LlamaIndex, custom implementations

Programming & Tools

  • Languages: Python, SQL, Bash
  • MLOps: MLflow, Weights & Biases, Kubeflow
  • Monitoring: Prometheus, Grafana, DataDog
  • Version Control: Git, DVC

Texas Energy Data Pulse

Data-driven analysis of Texas AI infrastructure and energy systems

20-dashboard series exploring how power becomes intelligence—from the Texas grid to orbital compute. Each visualization tells a story about infrastructure transformation.

Highlights:

  • TX-1 Orbital Prototype: Compute leaving Earth’s surface
  • Vector database performance at scale
  • Agentic AI system architecture patterns

View the complete series →

GitHub Portfolio

25+ repositories demonstrating production ML and infrastructure capabilities

  • Petabyte-scale data pipelines with medallion architecture
  • Production RAG implementations
  • Multi-cloud Terraform modules
  • ML system deployment patterns

Explore projects →

Certifications

Current:

  • AWS Solutions Architect Professional
  • AWS Advanced Networking Specialist
  • GCP Professional Cloud Architect
  • Azure AI Engineer Associate
  • Databricks Data Engineer Associate
  • Databricks Agentic AI Fundamentals
  • Oracle Agentic AI Professional

In Progress (Dec 2024 - Feb 2025):

  • AWS Solutions Architect Professional (recertification)
  • GCP Professional Cloud Architect (recertification)
  • AWS Advanced Networking (recertification
  • Databricks Machine Learning Professional
  • Databricks Data Engineer Professional

I love to work. Not because I have to—because I genuinely enjoy building systems that solve real problems. Give me a production deployment challenge at 6pm on Friday and I’m excited, not annoyed. Austin-based. Solving production ML problems today.

Connect on LinkedIn View code on GitHub