Research Scientist Graduates – LLM Foundation Models – Reasoning – Planning & Agent – Doubao – PhD

Research Scientist Graduates – LLM Foundation Models – Reasoning – Planning & Agent – Doubao – PhD

Requirements

• Currently pursuing a PhD in computer science, mathematics, engineering, or a related field
• Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, winners of competitions such as ACM/ICPC, NOI/IOI, Top Coder, Kaggle, etc. are preferred;
• Familiar with NLP, CV-related algorithms, technologies, and familiar with large-scale model training and RL algorithms are preferred;
• Candidates who have led influential projects or papers in the field of large-scale models are preferred.

Responsibilities

• Reasoning and planning for foundation models. Enhance reasoning and planning throughout the entire development process, encompassing data acquisition, model evaluation, pretraining, SFT, reward modeling, and reinforcement learning, to bolster overall performance.
• Synthesize large-scale, high-quality (multi-modal) data through methods such as rewriting, augmentation, and generation to improve the abilities of foundation models in various stages (pretraining, SFT, RLHF).
• Solve complex tasks via system 2 thinking, leverage advanced decoding strategies such as MCTS, A*.
• Investigate and implement robust evaluation methodologies to assess model performance at various stages, unravel the underlying mechanisms and sources of their abilities, and utilize this understanding to drive model improvements.
• Teach foundation models to use tools, interact with APIs and code interpreters. Build agents and multi-agents to solve complex tasks.

Preferred Qualifications

• 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.