Job Description

About the Team
The Seed Infrastructures team oversees the distributed training, reinforcement learning framework, high-performance inference, and heterogeneous hardware compilation technologies for AI foundation models.

Responsibilities
- Design, implement, and maintain agent execution environments and runtime frameworks for multi-agent training at scale
- Build and optimize infrastructure for RLHF pipelines, reward modeling, and distributed RL training
- Manage and orchestrate many-agent parallel execution, including environment simulations and environment managers
- Collaborate closely with research teams to support the LLM training pipeline: training → SFT → RLHF → evaluation → serving
- Ensure high-performance, scalable, and fault-tolerant distributed systems for agent frameworks
- Develop tools and libraries to monitor, debug, and benchmark agent training and inference
- Translate research prototypes into production-ready infrastructure that can support large-scale AI experiments

The base salary range for this position in the selected city is $232560 - $427500 annually.