Student Researcher - (Seed Infra-Compiler) - 2026 Start (BS/MS)

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.

As a project intern, you will have the opportunity to engage in impactful short-term projects that provide you with a glimpse of professional real-world experience. You will gain practical skills through on-the-job learning in a fast-paced work environment and develop a deeper understanding of your career interests.

Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

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