Student Researcher - Compiler (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/>- Contribute to AI compiler optimizations for training and inference workloads<br/>- Develop and extend MLIR-based compiler passes for graph lowering, optimization, and code generation<br/>- Optimize model execution on GPU and NPU accelerators, focusing on performance, memory efficiency, and scalability<br/>- Support model deployment pipelines, including compilation, packaging, and runtime integration<br/>- Assist with distributed training and inference acceleration, such as parallel execution, communication optimization, and runtime scheduling<br/>- Benchmark, profile, and analyze performance of large-scale models across different hardware backends<br/>- Collaborate with researchers and engineers to translate model and system requirements into compiler and runtime improvements<br/><br/> annually.<br/>