I’m Gerlando, an MSc graduate in Computer Science from Politecnico di Milano, awarded 110/110 with Honours.
🔭 My Master’s thesis on Multi-Armed Bandits in non-stationary environments was accepted at the European Conference on Machine Learning (ECML 2021), with an acceptance rate of approximately 20%.
💼 I currently work as a freelance AI Engineer, developing AI-driven projects and applications. Previously, I worked as a Machine Learning Engineer at Machine Learning Reply, focusing on Generative AI and NLP, and as a Data Engineer / Data Scientist at Target Reply, where I led multiple projects in the fintech domain.
📖 My primary interests include Artificial Intelligence, Machine Learning, Robotics, and Software Engineering, though I’m passionate about many areas of Computer Science. I enjoy programming challenges and continuously improving my coding skills.
In my spare time, I explore and implement new ML and AI techniques. This repository serves as a snapshot of my background and showcases some of the projects I’ve worked on over the years.
C/C++, Java, Python
ML/DL related
- Scikit-learn
- TensorFlow
- Keras
- PyTorch
- OpenCV
- Scikit-image
NLP & Generative AI
- Hugging Face Transformers
- Sentence Transformers
- spaCy
- nltk
- OpenAI/Gemini/Claude APIs
- Langchain/Langgraph ecosystem
Data & Visualization
- NumPy
- Pandas
- Polars
- Matplotlib
- Seaborn
AI Engineering & MLOps
- FastAPI
- Docker
- MLflow
- Weights & Biases
Vector Databases & Retrieval
- FAISS
- ChromaDB
- Qdrant
- Milvus
Distributed & Scalable Processing Systems
- Apache Flink
- Apache Spark
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🎯 Object Detection & Vision Models
Vision Transformers (ViT, Swin), diffusion-based vision models -
🧠 Generative AI & Large Language Models
Fine-tuning and alignment techniques (LoRA, QLoRA, instruction tuning)
Retrieval-Augmented Generation (RAG)
Agentic systems and tool-augmented LLMs -
📝 Natural Language Processing
Transformer optimizations -
🤝 Recommender Systems
bandit-based and reinforcement learning approaches -
⚙️ AI Engineering
Scalable inference pipelines
LLM-serving architectures
Monitoring, evaluation, and deployment of GenAI systems