About

• Conduct cutting-edge research in large foundation models, focusing on applying large foundation models in specific domain. Collaborate with cross-functional teams to integrate solutions into Artificial Intelligence (AI) -driven system. Develop and maintain research prototypes and software tools, ensuring that they are well-documented and adhere to best practices in software development. Publish research findings in top-tier conferences and journals and present your work at industry events. Collaborate with other AI researchers and engineers, sharing knowledge and expertise to foster a culture of innovation and continuous learning within the team. Embody our culture and values. Doctorate in relevant field AND 3+ years related research experience 3+ years experience in research related to Artificial Intelligence or Machine Learning. Doctorate in relevant field AND 5+ years related research experience OR equivalent experience. Experience publishing academic papers as a lead author or essential contributor. Experience participating in a top conference in relevant research domain. Background in system and architecture, including experience with computer hardware, software, and networking technologies. Deep knowledge about the latest large model training/inference technology such as instruction finetuning, Reinforcement Learning (RL) and Reinforcement Learning with Hindsight Experience Replay (RLHF), processed and self-reward modeling, low-precision training/inference, etc. A track record of published research in the field of AI or other system innovation is a plus. Keen interest in general AI research, including but not limited to large foundation models.