The Seed LLM Horizon Team is dedicated to developing the next-generation agent foundation model and building self-evolving, personalized Agent.
Requirements
- Research experience in one or more of the following: reinforcement learning, LLM agents, memory systems, tool use, or interactive learning.
- Strong coding skills and proficiency with modern deep learning frameworks.
- Demonstrated ability to conduct independent research, with publications in top-tier ML/AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP etc.
- Experience with long-horizon reasoning, multi-turn tasks, or asynchronous agent behavior.
- Familiarity with agent evaluation, personalization, or real-world tool integration.
- Background in building or analyzing large-scale agent training pipelines.
Responsibilities
- Enable models to perform deep usage of professional tools (e.g., search, code-interpreter) to solve complex problems.
- Develop approaches to generalize model abilities to millions of out-of-distribution (OOD) tools and scenarios.
- Scale up multi-turn tool-use training tasks and explore effective training methods.
- Address challenges of long-horizon, multi-turn tasks in reinforcement learning.
Other
- Currently pursuing a PhD in Computer Science, Software Engineering, Machine Learning, or a related field.
- Ability to collaborate effectively in a fast-paced, research-driven team environment.
- Please state your availability clearly in your resume (Start date, End date).
