Improving Reasoning Efficiency: While maintaining high reasoning quality, improving reasoning efficiency is another critical challenge. Efficient reasoning directly impacts the model's practicality and cost-effectiveness in real-world applications. Approaches such as knowledge distillation (transferring knowledge from complex models to smaller models) can be explored to reduce computational resource consumption, or the use of Long Chain-of-Thought (Long-CoT) techniques to improve Short-CoT models to balance reasoning accuracy with computational efficiency.
PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields preferred or strong industry experience in similar fields, ideally with familiarity with Asia-Pacific/Singapore research resources.
Solid foundation in machine learning and deep learning, with solid understanding of fundamental theories and methods in information retrieval, search and recommendation systems, and natural language processing/large language model etc.
Here, you'll tackle some of the most challenging algorithmic problems in real-world global business scenarios, including multilingual understanding, cross-cultural relevance, cold-start challenges, and cross-domain understanding.
Explore the application and implementation of cutting-edge research such as large language models, graph neural networks, and multimodal techniques in financial risk scenarios.
PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields preferred or strong industry experience in similar fields, ideally with familiarity with Asia-Pacific/Singapore research resources.
Build multimodal RAG systems, including development and optimization of key modules such as recall, ranking, long-text processing, and multi-document synthesis.
Drive the automation and scaling of evaluation workflows. Build sustainable evaluation platforms and toolchains to support high-frequency, stable evaluation needs during rapid model iteration.
Continuously track and incorporate the latest advances from academia and industry in areas including world models, generative simulation, reinforcement learning, planning and decision-making, and apply them to optimize existing simulation and algorithm pipelines;
If you are passionate about using cutting-edge algorithms to solve real-world challenges, join us in building a community where people around the world feel confident expressing themselves and can trust the space they share.