About
I am a Machine Learning Engineer focused on designing and operating production-grade, end-to-end ML systems on Google Cloud Platform.
I am leading the development of ML workflows spanning data modeling, feature engineering, training, deployment, and monitoring. I work primarily with Python, PyTorch, BigQuery, PostgreSQL, Docker, Terraform, REST APIs, and GitHub. I have also delivered analytical dashboards to meet client and business needs.
I approach problems with first-principles thinking: focusing on system boundaries and failure modes before selecting models or architecture. Beyond hands-on development, I own architectural decisions for ML systems and Data Pipelines, review designs and code, and help define standards for model development and ML infrastructure. I regularly mentor engineers, lead knowledge transfer sessions, and raise the quality bar across performance, cost efficiency, and long-term maintainability.
I am currently looking to grow into senior-level machine learning roles where I can continue to have impact through technical leadership, system design, and mentorship.
Outside of work, I enjoy playing Chess, Making DIY Diaries, and Doing Origami.