Research Engineer Graduate - 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: - Individuals who are completing or have recently completed a PhD degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline. - Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc. - Experience in distributed systems, large-scale training infrastructure, or ML systems. - Familiarity with deep learning frameworks and system optimization. Preferred Qualifications: - Strong problem-solving and engineering skills. - Strong communication and collaboration skills.