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

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 - As an Infrastructure Intern, you may work on one or more of the following areas: - Assist in building and optimizing large-scale distributed training systems (e.g., data/model parallelism, memory efficiency, reliability) - Support the development and improvement of reinforcement learning training pipelines and post-training systems - Improve inference performance, including latency, throughput, and system stability - Contribute to compiler or runtime optimizations for GPU and other accelerators - Conduct performance analysis, profiling, benchmarking, and bottleneck identification - Develop internal tools and automation to improve infrastructure efficiency and developer productivity - Collaborate with researchers and engineers to translate model requirements into scalable system solutions

Qualifications

Minimum Qualifications: - Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related technical fields - Proficiency in at least one programming language such as Python or C - Familiarity with machine learning frameworks such as PyTorch or similar tools - Strong analytical and problem-solving skills - Ability to work collaboratively in a fast-paced technical environment - Interest in pursuing long-term work in ML systems or AI infrastructure