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

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