I am a highly analytical AI Engineer specializing in Generative AI, Computer Vision, and Probabilistic Modeling. My professional edge is built on the intersection of rigorous technical research and a multiyear career in Strategic Consulting and Global Finance (Citibank, UniCredit).

I don't just build models; I architect production-ready AI systems where technical precision meets business governance. My work focuses on high-fidelity RAG, hybrid transformer architectures, and generative density estimation.

• Email: fvalerii@gmail.com
• LinkedIn: linkedin.com/in/fabriziovalerii
• Location: Panama City, Panama

• GGenerative & Agentic AI: LangChain (LCEL/Agentic), Model Context Protocol (MCP), Diffusion Models, IBM Watsonx, Semantic Reranking, Prompt Engineering (XML Grounding).
• Computer Vision: Vision Transformers (ViT), Hybrid CNN-ViT Architectures, ResNet, Image Processing (OpenCV).
• Deep Learning & Probabilistic: PyTorch, TensorFlow/Keras, TensorFlow Probability, VAEs, Normalizing Flows, Seq2Seq (LSTM).
• Classic ML & Analytics: XGBoost, Random Forest, Predictive Modeling, Threshold Optimization (Precision-Recall tuning).
• Vector Databases: ChromaDB (Persistent), FAISS (In-memory).
• Data Science & Ops: Python (Expert), SQL, uv (DevOps), Knowledge Graphs (Neo4j), Geospatial Data.

• Core Logic: Dual-Backend RAG with Multi-Tenant Isolation.
• Achievements: Built two alternative pipelines (Watsonx/Granite-4 vs. Llama-3.1). Implemented Two-Stage Retrieval using Cross-Encoder Reranking and PDF hashing for session isolation. Optimized for zero-hallucination technical analysis via specialized XML grounding.

• Core Logic: Benchmarking Framework Parity (PyTorch vs. TensorFlow).
• Achievements: Integrated CNN feature extractors with Transformer self-attention blocks to capture global spatial relations. Achieved >99% accuracy and 1.000 ROC-AUC across both framework implementations.

• Core Logic: Generative Latent Space Organization.
• Achievements: Used Normalizing Flows for custom data generation and a VAE with $\beta$-weighting to force clear latent-space organization. Validated performance with a 0.4473 FID score, proving near-identical statistical distribution to real data.

• Core Logic: Custom Encoder-Decoder via TensorFlow Subclassing.
• Achievements: Scaled to 200,000+ sentence pairs using asynchronous prefetching. Achieved a 17.32 BLEU Score using a 512-unit LSTM engine with Orthogonal Initialization and asymmetric dropout profiles.

• Core Logic: Threshold Optimization for Business Retention.
• Achievements: Developed XGBoost ensembles achieving 97% Precision. Performed decision threshold tuning (optimized to 0.089 for Waze) to prioritize Recall and identify at-risk users, delivering actionable "burnout" and "churn" roadmaps for HR/Finance.

• MITx Micromasters in Statistics and Data Science (In Progress, MIT/edX)
  • Completed: Probability - The Science of Uncertainty (6.431x) and Machine Learning with Python (6.86x).
• STATSX0001: Statistical Learning (Stanford Online)
• Degree in Management Engineering (Politecnico Di Milano)

Before transitioning full-time into AI, I built a career in finance and business consulting and strategic management.

• Chairman and Owner, Strategic Project Overseas Inc.: Oversaw private equity investments in young technology companies, focusing on strategic valuation and operational due diligence.
• Equity Trader (Independent): Developed and executed proprietary investment strategies based on technical and fundamental analysis of financial markets.
• Organization Manager, Pioneer Global Asset Management: Coordinated large-scale business rationalization, process optimization, and project management (PRINCE2) for Asset Management division of the UniCredit Group.
• Senior Business Consultant, PWC Consulting: Participated in projects in the financial sector in the areas of strategy, company restructuring, and implementation of IT systems.
• Telephone Banking Head, Citibank: Implemented the Telephone Banking unit of Citibank in Italy from the ground up and subsequently managing its operations.

• Model Context Protocol (MCP) Mastery (Jan 2026, Anthropic/Fractal Analysis)
• Building Diffusion Models (Jan 2026, Fractal Analysis)
• IBM RAG & Agentic AI Professional Certificate (Dec 2025, IBM)
• Google Cloud Professional Machine Learning Engineer (Nov 2025, Google)
• IBM GenAI Engineering Professional Certificate (Oct 2025, LangChain/Watsonx)
• IBM Deep Learning Professional Certificate (Oct 2025, PyTorch/TensorFlow)
• TensorFlow 2 for Deep Learning Specialization (Jan 2025, Imperial College London)
• Google Advanced Data Analytics Professional Certificate (Oct 2024, Google)
• Google Data Analytics Professional Certificate (July 2024, Google)

Polyglot: Italian (Native), English, Spanish, Portuguese, French, German.