Software Engineer Intern - AI Infra Compute

About the team: Compute division focuses on building large-scale and highly available cloud infrastructure, which supports both public cloud products (like VolcEngine ECS service) and the internal products. Compute-US team focuses on the development and research of the compute infrastructure platform. We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals. Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates. Responsibilities: - Explore and develop key technologies for our AI Infra stack, including AI training and inference platforms, AI Agent infrastructure, etc. - Build prototypes to verify the functionality and performance of key components or innovations. - Showcase our research findings and products through academic publications. Minimum Qualifications: - Currently pursuing a Master in Software Development, Computer Science, Computer Engineering, or a related technical discipline. - Experience in at least one of the following areas: LLM training/Inference, Physical AI Infra(training, inference, simulation, RL, synthetic data, etc). - Ability to work independently and complete projects from beginning to end and in a timely manner. - Good communication and teamwork skills to clearly communicate technical concepts with other teammates. Preferred Qualifications: - Code contributions to open source communities like Pytorch, vLLM or SGlang. - Publications in relevant computer science conferences such as OSDI or MLSYS.