Computer Science graduate and AI & Data Engineer focused on building intelligent systems that transform complex business processes into scalable, data-driven solutions.
My experience spans Data Engineering, Machine Learning, MLOps and Cloud Architecture, working across the entire AI lifecycle—from data ingestion and infrastructure design to model deployment and operationalization.
Currently working on enterprise-scale AI and Data initiatives involving cloud platforms, data lakes, intelligent document processing and Generative AI applications.
- Machine Learning
- Deep Learning
- Generative AI
- Large Language Models (LLMs)
- Intelligent Document Processing
- OCR & NLP
- Anomaly Detection
- Feature Engineering
- Data Pipelines
- ETL / ELT
- Data Lakes
- Data Warehousing
- Data Modeling
- Apache Airflow
- Apache Spark
- BigQuery
- Dataform
- Model Deployment
- ML Pipelines
- MLflow
- Docker
- Terraform
- AWS
- Google Cloud Platform (GCP)
- Amazon Bedrock
- Python
- SQL
- TypeScript
- Flask
- REST APIs
- Git
- AI | ML Engineering
- Machine Learning in Production
- MLOps
- Generative AI & LLM Applications
- Cloud-Native Data Platforms
- Intelligent Process Automation
- Multi-Agent AI Systems
Machine Learning system designed to support effort estimation and project planning through predictive analytics.
Document-aware chatbot powered by Large Language Models running entirely on local infrastructure.
AI-driven platform for monitoring geopolitical events and assessing supply chain impacts.
End-to-end AI pipeline combining OCR, NLP and LLMs to extract, classify and infer information from unstructured documents.
My goal is to become a technical leader in Artificial Intelligence, building production-grade AI systems that combine Machine Learning, Data Engineering and Cloud Architecture to solve high-impact business problems.
- LinkedIn: www.linkedin.com/in/saviom3ndes
- Email: savioAlexandre.22@hotmail.com