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

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

• 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
• Develop performance analysis, profiling, benchmarking, and bottleneck identification tools
• Contribute to 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

• 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