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.

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

annually.