I'm a software engineer focused on system architecture and machine learning. I actively study how major open-source codebases are built to write robust, production-grade systems, and I use ML/DL where it's the only real solution to the problem.
⚡ What I Know & How I Build
- System Design & Architecture — deep in HLD and LLD, studying patterns across the stack rather than staying inside one framework's defaults.
- Reading for mental models — I actually love reading technical engineering books and dissecting large open-source repos to write idiomatic, production-efficient code, not just correct code.
- ML/DL — Building and training models from scratch, focusing on the mathematical fundamentals to solve real-world problems that are uniquely suited for AI.
- A hacker's eye — I approach architecture and models edge-case-first, a habit from my background in offensive security.
🔭 Currently Working On
- Open-source core contributions — Active contributor and code reviewer across the foundational PyData & machine-learning ecosystem (NumPy, scikit-learn, pandas, statsmodels...).
- Systems Programming & DSA — Developing a custom command shell in C to deepen my understanding of low-level process creation, I/O redirection, and OS-level execution along with Data Structures and Algorithms.
- Algorithmic Architecture — Engineering a multi-agent autonomous trading pipeline in Python using LangGraph to dynamically evaluate market conditions and sentiment.
💬 i'm always happy to talk and network with new people to collaborate and collect new insights.
