I started my career in signal engineering, working with audio processing and time series analysis. The mathematical rigor of signal processing naturally led me to explore machine learning and AI. Over the years, I've built end-to-end ML systems - from research and prototyping to deployment on AWS and GCP. My work spans NLP, computer vision, and classical ML, with a special focus on problems where signal processing meets deep learning.
I believe in engineering best practices: CI/CD pipelines, thorough testing, clear documentation. I've worked in agile teams and thrive in collaborative environments where knowledge sharing is the norm.
Currently open to opportunities where I can apply this blend of signal processing expertise and ML engineering. Contact me if you'd like to collaborate.