Student Researcher (AI Foundation Models Infrastructure - Seed Infra) - 2026 Start (PhD)

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
- As an Infrastructure Intern, you may work on one or more of the following areas:
- Design and optimize large-scale distributed training systems (e.g., data/model/pipeline parallelism, memory efficiency, fault tolerance)
- Contribute to reinforcement learning training frameworks and large-scale post-training systems
- Improve inference performance, latency, and throughput for foundation models
- Develop compiler or runtime optimizations for heterogeneous hardware (GPU/accelerator)
- Work on system-level performance analysis, profiling, and bottleneck diagnosis
- Build tooling and automation to improve developer productivity and system reliability

annually.