I see myself as a problem-solver with a can-do attitude

I've been passionate about computers and software my entire life, which has led me to explore a wide range of topics and continuously broaden my knowledge.
My background is in traditional software development, where I focus on delivering high-quality projects with clean, maintainable code. I prioritize automation, DevOps practices, and continuous integration. In my work, I aim to apply these principles through well-documented code, efficient build and test pipelines, and the use of containerization and Infrastructure as Code (IaC).

Data is a key aspect of IT, which sparked my interest in machine learning and data science. I've worked with various data processing tools, built predictive models, and utilized statistical methods to extract valuable insights from data.
Given that many machine learning models and software solutions are deployed in the cloud, my experience extends to cloud technologies, including managing cloud infrastructure, container orchestration, and automating deployment pipelines.