About Me
Transitioning from Full-Stack Engineering to Machine Learning, bringing a production-first mindset to applied ML.
Professional Narrative
I started my career as a Full-Stack Engineer, building robust web applications and scalable systems. My passion for impact and curiosity about data-driven solutions led me to transition into Machine Learning, where I now focus on applied ML and productionizing models end-to-end.
- Full-Stack background: System design, APIs, cloud infrastructure, frontend & backend development
- Why ML: Impact, automation, and solving real-world problems with data
- How I'm proving it: 4 end-to-end ML projects, metrics-driven approach, production mindset
Transition Timeline
Full-Stack Engineer
2017–2023
Built web applications, REST APIs, and cloud-based systems. Gained expertise in system design, deployment, and end-to-end product delivery.
ML Exploration
2022–2023
Self-study in machine learning fundamentals, completed ML courses, experimented with models, and discovered passion for applied ML.
Applied ML Engineer
2023–Present
Building end-to-end ML projects, focusing on production ML, model evaluation, and deployment. Combining software engineering strengths with ML expertise.
Let's Connect
Want to learn more or discuss opportunities?