Principal Engineer
CurrentProjects as Principle Engineer, Software Development (Apps)Current Projects: SV Calibration Data project, which leverages machine learning to continuously improve model performance while detecting anomalies. Key highlights of the project include: Initial Proof of Concept: Implemented supervised learning using a 1D Convolutional Neural Network (CNN) to establish the foundation. Current Model Overview: Developed and maintained a detailed overview of the latest model version in PoC, MVP and production. Phase 1: Designed a Transfer Learning Pipeline to enable continuous retraining and anomaly detection, adapting the model to evolving data. Phase 2: Built a hybrid Semi-Supervised/Transfer Learning Pipeline to further enhance model performance and anomaly handling.Older projects: Led the zero-to-pilot implementation of an on-premises hybrid cloud solution for testing APIs before moving to Google Kubernetes Engine (GKE). This served as an R&D testing cluster for data engineering pipelines, Infrastructure as Code (Linux), CI/CD, and ML DevOps in a Kubernetes environment.Developed the DAO Horizon SIEVE, an automated paper screening app for the Horizon platform used on the manufacturing HDD floor in Thailand. This project utilized Kafka for real-time data streaming and automated user queries.Tech Lead and Project Leader for GalaXY – Guided Data Discovery Platform Development, scaling MVP1 to support over 100 users, mentoring team members, and optimizing the web application layer to achieve a 10x speed improvement.
