Research Scientist Graduate (Seed Model - LLM) - 2026 Start (PhD)

About The Team

LLM team is dedicated to advancing the next generation of LLMs and solving, fundamental challenges in LLM development. Our areas of focus include model pretraining, posttraining, inference, memory capabilities, learning, interpretability and other related directions. We dive deep into the latest technologies and create comprehensive solutions from concept to completion. In our endeavor to adopt LLMs in real-life scenarios, we explore methods to enhance applications through technological innovation.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Responsibilities

• Explore large-scale models and optimize systems;
• Data construction, instruction tuning, preference alignment, and model optimization;
• Improving relevant model capabilities, such as reasoning, coding, and math, etc.;
• In-depth research and exploration of future use cases.

Minimum Qualifications

• Individuals who are completing or have recently completed a PhD degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline.
• Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc.

Preferred Qualifications

• Experience with large-scale model training, deep learning and machine learning algorithms are preferred;
• Candidates who have led influential projects or papers in the field of large-scale models are preferred;
• Excellent problem analysis and solving skills, able to deeply solve problems in large-scale model training and application;
• Good communication and collaboration skills, able to explore new technologies with the team and promote technological progress.