Construct multimodal semantic links across video-product, product-product, and video-video relationships to support trend understanding, product mining, AIGC generation, and content-commerce supply optimization.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.
Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
Next-Gen Marketing Tech: Go beyond traditional discriminative uplift prediction. Research and productionize cutting-edge causal inference and AI technologies — including Uplift Modeling, E2E Modeling, RL, LLMs, and AI Agents — to directly address user conversion and repeat purchase behavior.
As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The Research Fellow / Research Engineer will support a research project focused on the development of data-driven modelling, optimisation, and decision-support tools for food and nutrition systems. The successful candidate will work closely with the Principal Investigator on research activities involving data analytics, computational modelling, machine learning, and optimisation. The role offers opportunities to contribute to research publications, technical development, and industry-relevant project outcomes in the areas of food sustainability, nutrition, and supply chain decision-making.
Engineer Enterprise Knowledge Systems: Build and maintain knowledge platforms spanning codebases, architecture repositories, documentation, operational runbooks, and post-mortems to power context-aware AI agents and workflows.