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

Contribute to infrastructure and systems for large-scale models.
Support development of efficient and scalable components across areas such as training platforms, inference systems, compilers, and distributed systems.
Implement and optimize system modules, tooling, or frameworks.
Collaborate with researchers and engineers to support research and system development.

Minimum Qualifications

Currently pursuing a Bachelor's or Master's degree in computer science, mathematics, engineering, or a related field.
Strong programming skills and solid foundation in algorithms, data structures, and systems, proficient in Python or C/C++.
Experience with systems programming, distributed systems, compilers, or performance optimization through coursework, research, or projects.

Preferred Qualifications

Experience with large-scale systems, parallel or distributed computing, or performance optimization. Familiarity with system design, debugging, and profiling tools.
Strong problem-solving ability and ability to work collaboratively in a technical environment.