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Achievements

Achievement: Pull SharkAchievement: Pair Extraordinaire

Achievements

Achievement: Pull SharkAchievement: Pair Extraordinaire

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dtortosa/README.md

Diego Salazar Tortosa | AI Engineer

I bring scientific rigor to production AI systems. With over a decade of experience handling complex datasets and building machine learning models, I design backend architectures and AI workflows built to run at scale.

🛠️ Tech Stack & Core Competencies

  • AI Engineering: LLM Applications, Production RAG Systems, AI Agents, LangChain, Framework-Free Execution Loops, Prompt Engineering, Structured Outputs (Pydantic), Vector Databases (pgvector, FAISS), LLM evals
  • Machine Learning & Evaluation: Deep Neural Networks, Tree-Based Ensembles (XGBoost, Random Forest), Ensemble Stacking, Bayesian Inference, Nested Cross-Validation, Hyperparameter Optimization, Explainable AI (XAI)
  • Infrastructure & Backend: FastAPI, PostgreSQL, Celery, Azure, Docker, Cloud Deployments, Git/GitHub Actions
  • Scientific Computing: Python, PySpark, Numpy, Pandas, R, Bash, Parallel and Distributed Processing

📈 Featured Architectures

  • Production RAG & Automation Engines: Event-driven, containerized microservices for processing unstructured documents.
  • Distributed Scientific Pipelines: Parallel architectures built with PySpark and multiprocessing to handle hundreds of gigabytes of high-dimensional data.

Pinned Loading

  1. ai-business-intelligence-assistant ai-business-intelligence-assistant Public

    AI agent that combines sales data analytics (Pandas), document retrieval (FAISS RAG), and execution monitoring in a Streamlit dashboard.

    Jupyter Notebook

  2. hr-knowledge-rag-agent hr-knowledge-rag-agent Public

    RAG pipeline that chunks documents, stores them in a Chroma vector database, and adds web context for specific topics. Built with LangChain, Jinja2, and Gradio.

    Jupyter Notebook

  3. twitter-forex-ml-pipeline twitter-forex-ml-pipeline Public

    Machine learning pipeline that scrapes tweets (snscrape), builds sentiment indexes, and predicts the EUR/USD exchange rate.

    Jupyter Notebook

  4. novel-ml-framework-genetic-adaptation novel-ml-framework-genetic-adaptation Public

    ML framework that benchmarks deep learning and tree ensembles on 180 GB of data using Slurm HPC clusters, nested cross-validation, and explainable AI.

    Python

  5. genome-wide-analysis-trainability-australia genome-wide-analysis-trainability-australia Public

    Distributed genomic pipeline that processes a 3.85B-genotype matrix with PySpark and HPC, running multi-model polygenic scoring with 100-fold validation.

    Python

  6. novel-ml-method-climate-change-prediction novel-ml-method-climate-change-prediction Public

    Novel geospatial machine learning framework that runs 100k+ combinatorial scenario projections across IPCC climate pathways, using model ensembles and out-of-distribution validation.

    R