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Building Data & AI Platforms
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Building Data & AI Platforms

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patricksferraz/README.md

Computer

Hi there, I'm Patrick Ferraz 👋

I am a Data & AI Engineer and Tech Founder specializing in high-impact Data & AI Platforms and systems architecture. My work focuses on driving digital transformation across multi-cloud environments (AWS, Azure, GCP). I am also actively researching Quantum Machine Learning (QML) at the Master's level.

My expertise spans the entire product lifecycle, from R&D and foundational architecture to robust MLOps/DevOps implementation:

  • Principal Focus: Architecting and implementing scalable Big Data, AI, and Cloud Platforms.
  • Innovation: Advanced research in QML and practical application of Generative AI (GenAI) & LLMs.
  • Leadership: Technical and strategic leadership, establishing Data Areas from scratch and founding tech Startups.
  • Engineering & Ops: Deep proficiency in Software Engineering (Go, Python, TypeScript) and implementing robust DevOps, DataOps, and MLOps practices.
  • Current Research: Quantum Machine Learning (QML) and Quantum Computing.

Core Stack & Research Focus

I operate across multi-cloud infrastructure and a specialized stack designed for performance and scale.

Python Golang Typescript Apache Spark Databricks AWS Azure GCP Terraform Kubernetes TensorFlow PyTorch PostgreSQL Apache Kafka Prometheus React Qiskit

I also work with:

  • Research & Advanced Topics: Quantum Machine Learning (QML), Quantum Computing, GenAI/LLMs, HPC, Atmospheric Models (WRF, Geoschem).
  • Data Systems: Databricks, Spark, Data Factory, Airflow, Streaming (Kafka), SQL/NoSQL (PostgreSQL, MongoDB), SAP Ecosystem.
  • Cloud Native & DevOps: IaC (Terraform), CI/CD (GitHub Actions, Azure DevOps), Observability (Prometheus, Grafana), Kubernetes, Kong, Key Vault, Edge Compute.
  • Development & Visualization: React/Angular, TypeScript, Golang, Plotly Dash, PowerBI, Streamlit.

Projects & Contributions

I consistently lead the development of critical Big Data and AI platforms, driving business value, and actively contribute to R&D&I projects focused on pioneering solutions, multi-cloud platforms, and advanced research.

Find Me On:

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GitHub Stats

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@patricksferraz

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  1. mstuttgart/brazilcep mstuttgart/brazilcep Public

    🇧🇷 Minimalist and easy-to-use Python library designed to query CEP (Postal Address Code) data.

    Python 236 59

  2. barronh/pseudonetcdf barronh/pseudonetcdf Public

    PseudoNetCDF like NetCDF except for many scientific format backends

    Python 81 35

  3. CRIA-CIMATEC/covid-19 CRIA-CIMATEC/covid-19 Public

    IA-COVID-19 Project

    Jupyter Notebook 9 3

  4. pkoliveira/pyaiutils pkoliveira/pyaiutils Public

    Python 5 1