Fullstack AI Engineer, Deep Learning, Computer Vision

Spearheaded and led AI & Data Science team of 4 members. Built DS & AI capabilities from scratch including invoice/document parsing & OCR, a GenAI (LLM) powered chatbot for insurance policy documents (RAG architecture), Recommendation System, Demand Forecasting, and ML automation of adjudication. Responsible for AI strategy, roadmap & hiring. Drove cross-functional AI initiatives with C-level leaders. Established ML best practices using Vertex AI and Kubeflow pipeline. Received AI Trailblazers award from Singapore Ministry of Digital Development and Information & Google.

Guest lecturer on deep learning, data science, computer vision, and natural language processing.

Led Recommendation System & Competitive Intelligence for Southeast Asia. Directed a high-performing 7-member AI engineering team, defining core objectives and KPIs. Boosted CTR by 16%, DAU by 10%, GMV by 12%. Established best practices for end-to-end ML projects. Built large-scale recommendation system serving 100M+ users using algorithms including Boosting, ResNet, Inception, SiameseNet, Self-supervision MoCo, SwAV, Deep Metric Learning with TensorFlow, PyTorch, XGBoost, CatBoost, and Hive.

Led 4-member ML team in architecture, algorithms, and MLOps. Developed and deployed ML models including CNN-based models (ResNet, Inception) using PyTorch, TensorFlow, Sklearn, LightGBM, XGBoost for hotels onboarding efficiency and KYC accuracy with OCR and face recognition improvements. Led implementation of end-to-end ML projects including image query, face recognition, tourism image categorization, image captioning, deduplication, and image aesthetics scoring serving hundreds of millions of users.

Led data science & ML engineering team of 9 members delivering Deep Learning models for pattern recognition in medical image data. Led end-to-end ML projects covering architecture, model selection, training, feature engineering, evaluation, productionisation, and maintenance. Developed models for complex tissue and tumor pattern detection in immunohistochemistry data, improving F1 score by 52% and model development time by 3X. Implemented tissue pattern detection and segmentation in biomedical imaging using Keras, TensorFlow, OpenCV, Sklearn, LightGBM, and OpenSlide. Drove agile/scrum culture, CI/CD & TDD development, and MLOps implementation.

Developed and deployed ML algorithms (CNN) for complex tissue pattern detection and segmentation using Keras, TensorFlow, and OpenCV. Built and managed end-to-end ML pipeline covering architecture, model selection, feature engineering, evaluation, metrics, and workflow.

Prototyped and deployed object detection, scene layout analysis, and OCR using C++, Python, and OpenCV for the retail industry. Successfully delivered project to raise funding for the company.

Researcher at the Cluster of Excellence for Multimodal Computing and Interaction in Saarbruecken, Germany.

Researched and developed 3D multi-camera object detection algorithms. Implemented 3D multi-camera registration.

Awarded Best New Employee of The Year. Delivered impactful and challenging project with 1 million USD valuation.

Teaching Assistant at the Physics Lab of Pelita Harapan University in Karawaci, Indonesia.