Job Responsibilities
• Conduct research and optimization on technologies related to Visual Language Models (VLMs), embedding models, and AI Agents. The research scope includes, but is not limited to, model architecture design, performance enhancement, and platform deployment.
• Take comprehensively imprving model accuracy, efficiency, and scalability as the core goal, and promote the iterative optimization and practical verification of relevant technologies.
• Engage deeply in cutting-edge research on knowledge-based Retrieval-Augmented Generation (RAG), and explore innovative methods and technical approaches in fields such as document understanding, information retrieval, and multimodal perception.
Qualifications
• Educational Background: Master's degree or higher in Computer Science, Natural Language Processing, Artificial Intelligence, or a closely related field.
• Technical Capabilities: Proficient in Python and C++ programming languages, with solid software engineering practices and the ability to independently develop and optimize state-of-the-art models; experience in model deployment on hardware platforms is a plus.
• Research Foundation: Solid academic research background in visual language modeling or related domains, with a deep understanding of the principles and architectures of foundation models.
• Academic Achievements: Publication record in top-tier conferences (e.g., CCF-A venues such as NeurIPS, ICML, CVPR, ACL, etc.) is highly desirable.
• Project Experience: Prior experience with multimodal Retrieval-Augmented Generation (RAG) systems is preferred.
• Comprehensive Qualities: Excellent teamwork and communication skills, with the ability to collaborate effectively across diverse technical teams; highly self-motivated, with strong learning ability and the capacity to stay current with the latest industry technological advancements.