About

• arn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer. Conduct research on state-of-the-art artificial intelligence methodologies and identify new opportunities to advance artificial intelligence from various aspects. Leverage interdisciplinary expertise and knowledge across NLP, LLM, computer vision, and other related domains to accelerate innovation in artificial intelligence. Develop, prototype, and optimize novel methodologies to tackle the core challenges of artificial intelligence. Disseminate research findings through publications in peer-reviewed journals, top-tier conferences, and other relevant venues, and present results both internally and externally. Currently enrolled in a Master or Ph.D. program in Computer Science, Electrical Engineering, Mathematics or a related field. In addition to the qualifications below, you'll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter. Ability to work independently and collaboratively in a dynamic and vibrant research environment. Willingness to embrace knowledge/technique outside your field of research. Solid programming skill, including prototyping, implementation and optimization. Experience in LLM pre-training, post-training and inference (like Megatron framework). Experience in world model, multimodality and AI4Code. Reinforcement Learning experiences and frameworks (like VeRL, rLLM). Proven publication track such as CVPR, ACL, ICML, ICCV, ECCV, NeurIPS, ICLR, RSS etc.