Student Researcher (Seed - LLM - Model) - 2026 Start (PhD)

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 in 2026. PhD Internships at our Company aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies.

PhD internships at Our Company provides students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts.

Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

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.

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.