Building scalable AI platforms, modern data architectures and production-grade machine learning systems.
Designing and engineering scalable Data & Artificial Intelligence systems — from modern Lakehouse architectures to production-grade AI platforms.
I focus on engineering-first solutions combining:
- Large Language Models (LLMs)
- Deep Learning Systems
- Distributed Data Platforms
- Quantitative AI Models
- Production ML Infrastructure
- AI System Scalability
Production-oriented Artificial Intelligence systems built with a strong focus on scalability, modularity and real-world engineering.
- Transformer architectures implemented from scratch
- Retrieval-Augmented Generation (RAG)
- Vector Database pipelines
- LLM fine-tuning strategies (LoRA)
- Real-time inference pipelines
- Detection & tracking systems
- Deep Learning optimization workflows
- AI-driven trading systems
- Portfolio optimization models
- Risk modeling architectures
- Time-series forecasting
- Distributed training simulations
- Scalable ML workflows
- REST APIs & deployment architectures
- Experiment reproducibility pipelines
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Oracle Cloud Infrastructure Foundations Associate
Validated knowledge of:
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Oracle Cloud Infrastructure Data Platform Foundations Associate Validated knowledge of:
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Oracle Cloud Infrastructure AI Foundations Associate Validated knowledge of:
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Mathematics before abstraction
Framework-aware, not framework-dependent
Clean & scalable architecture
Production-grade implementation
Performance-driven optimization
Interested in building:
- Scalable AI Platforms
- High-Performance ML Systems
- Modern Lakehouse Architectures
- Enterprise AI Infrastructure
- Advanced Data Platforms
