Research Scientist - Seed Model, AI Foundation Model Infrastructure

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 - Design and build scalable infrastructure for large-scale model training, evaluation, and inference. - Optimize distributed training systems across compute, memory, and communication. - Improve system reliability, efficiency, and observability for large-scale workloads. - Develop frameworks for evaluation, data processing, and model lifecycle management. - Co-design systems and algorithms to improve performance of foundation models. Minimum Qualifications: - Currently pursuing a Bachelor's or Master's degree in computer science, mathematics, engineering, or a related field, with an expected graduation date in 2027 and the ability to commit to an onboarding date by the end of 2027. - Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc. - Demonstrated interest or project experience in relevant areas. Preferred Qualifications: - Experience in distributed systems, machine learning systems, or related areas through internships is preferred. - Strong problem-solving and collaboration skills.