Student Researcher Intern - Seed Model, LLM

Team Intro The Seed-LLM-Model team is dedicated to foundational algorithm research for LLM models, focusing on issues such as model architecture, optimization, and stability. This ensures the performance and efficiency of large model training and inference, providing a foundation for downstream tasks. We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date). Summer Start Dates: - May 11th, 2026 - May 18th, 2026 - May 26th, 2026 - June 8th, 2026 - June 22nd, 2026 Responsibilities - Participate in the research and development of cutting-edge algorithms with the possibility to publishing top international papers, and applying for patents. - Conduct in-depth research for cutting-edge technologies in the fields of large language models/MultiModal Machine Learning, and have opportunities for applying them to solve practical problems in the industry. Minimum Qualifications - Currently pursuing a PhD in artificial intelligence, computer science, automation, mathematics, or a related technical discipline. - Solid foundation in data structure and algorithm design, proficient in Python/C++, proficient in deep learning frameworks such as PyTorch and TensorFlow, proficient in distributed large language model training framework such as Megatron/FSDP/Deepspeed. - Good reading and writing skills and a solid foundation in mathematics. - Strong sense of responsibility, proactive, with good communication and teamwork skills. - Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment. - Must be able to commit to a 12-week full-time work period during Summer or Fall 2026. Preferred Qualifications - Pre-trained basic technologies, including efficient training and encapsulated deployment services, NLP, CV, video, MultiModal Machine Learning and other related pre-trained models and their downstream applications are preferred. - Candidates who have published papers in accredited academic conferences, and have achieved excellent results in competitions in the fields of MultiModal Machine Learning, Computer Vision, or Machine Learning are preferred. As a condition of employment, all successful candidates must be able to establish authorization to work in the United States. For this position, the Company does not provide sponsorship or any immigration-related benefits.