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sekR4/README.md

Hi there, I'm Sebastian! πŸ‘‹

πŸš€ Senior Data & AI Engineer | Building the Future with Data & AI

"I speak Python fluently, SQL natively, and I'm working on Korean... πŸ‡°πŸ‡· (turns out Korean is much is harder)"

πŸ”¬ What I Do

  • Senior Data & AI Engineer with a background as a Senior Data Scientist
  • Building end-to-end AI solutions from ETL pipelines to production APIs (+ sometimes a bit frontend)
  • Translating complex business problems into scalable data & AI architectures
  • Mentoring junior teammates and actively sharing knowledge across the company
  • Making technical concepts accessible to non-technical stakeholders

πŸ› οΈ Tech Stack

Core Languages & Frameworks

languages = ["Python", "SQL", "Bash", "TypeScript"]
ai_ml = ["OpenAI", "Scikit-learn", "Hugging Face", "TensorFlow"]
data_engineering = ["Sling", "Airflow", "dbt", "Kafka", "Apache Spark"]

Cloud & Infrastructure

  • ☁️ Cloud Platforms: AWS, Azure, GCP
  • πŸ—„οΈ Databases: DuckDB, PostgreSQL, MongoDB
  • 🐳 DevOps & MLOps: Docker, GitHub Actions, MLflow, AWS SageMaker
  • πŸ—οΈ Infrastructure as Code: OpenTofu/Terraform, Ansible, CloudFormation

Specialized Skills

  • πŸ€– GenAI & Vector Search: RAG systems, vector databases, retrieval architectures
  • ⚑ API Development: FastAPI, REST API design
  • πŸ”„ Automation: CI/CD pipelines, workflow orchestration
  • πŸ“Š Data Visualization: Evidence, AWS QuickSight, Tableau

🎯 Current Projects & Achievements

🌐 Full-Stack GenAI Translation API (Current)

Building a comprehensive translation system with:

  • Translation memory & retrieval systems
  • AI-powered evaluation (AI as a judge)
  • REST API architecture deployed on Azure
  • End-to-end MVP successfully delivered

πŸ“ˆ ML-Powered Reversal Prediction Model

  • Built first ML prototype in the company I worked for to predict reversals using domain expertise
  • Combined multiple data sources, derived features & targets (labels) and made XGBoost do its magic
  • Leveraged cross-functional knowledge (Data Engineering + Data Science)

⚑ MLOps Pipeline Optimization

  • Reduced model deployment time from 1+ week to 3 days
  • Automated evaluations with custom Python package
  • Enhanced GitLab workflows and CI/CD processes

πŸ₯’ Fun Facts

  • 🍜 Korean Food Enthusiast: My wife is Korean, and I'm convinced Korean cuisine is the ultimate fuel for coding sessions
  • πŸ—£οΈ Language Goals: Fluent in Python & SQL, intermediate in TypeScript, beginner in Korean (ν•œκ΅­μ–΄λŠ” μ–΄λ €μ›Œμš”! πŸ˜…)
  • β˜• Philosophy: Great data solutions are like great Korean BBQ - they bring people together and solve real problems

πŸ“« Let's Connect!

LinkedIn Bluesky Website


πŸ’‘ Always Learning, Always Building

"The best models aren't just technically soundβ€”they solve real problems and create genuine value. Whether it's predicting business outcomes or building the next generation of AI systems, I'm here to turn data into impact."


⭐ Fun Challenge: If you can help me debug my Korean pronunciation as easily as I debug Python code, let's chat! πŸ˜„

Pinned Loading

  1. FastAPI-on-Google-Cloud-Run FastAPI-on-Google-Cloud-Run Public

    Deploying a FastAPI app on Google Cloud Run

    Dockerfile 67 12

  2. Code-Assistant-Tests Code-Assistant-Tests Public

    Comparison of ai code assistance like Continue, Github Copilot & Windsurf

    TypeScript 1

  3. MLE MLE Public

    Code Snippets and Notes while working on the Machine Learning Engineer Nanodegree at Udacity

    Jupyter Notebook

  4. Automobile Automobile Public

    A regression example

    HTML

  5. Reproducible-Research Reproducible-Research Public

    This is the repo for the Reproducible Research course

    HTML 1

  6. Advent-Of-Code Advent-Of-Code Public

    Jupyter Notebook