Software Engineer Intern (Doubao (Seed) - Machine Learning System) - 2025 Summer (PhD)

Team Introduction
Established in 2023, the ByteDance Seed team is dedicated to discovering new approaches to general intelligence, and pushing the boundaries of AI. Our research spans large language models, speech, vision, world models, AI infrastructure, next-generation interfaces and more.
With a long-term vision and determination in AI, the ByteDance Seed team remains committed to foundational research. We aim to become a world-class AI research team that drives real technological progress and delivers societal benefits.
With labs across China, Singapore, and the U.S., our team has already released industry-leading general-purpose large models and advanced multimodal capabilities, powering over 50 real-world applications — including Doubao, Coze, and Jimeng.

We are looking for talented individuals to join us for an internship in 2025. Internships at Bytedance aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at ByteDance.

Internships at ByteDance aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. This Internship Program runs for 12 weeks beginning in May/June 2025.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to Bytedance and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities
This internship provides students the opportunity to join one of our engineering teams where you will have the opportunity to:
- Design and development of resource scheduling, including model training, model evaluation and model inference in various scenarios (LLM/AIGC/NLP/CV/Speech, etc.)
- Optimize orchestration of various computing resources (GPU, CPU, other heterogeneous hardware), realizing the rational use of stable resources, tidal resources, mixed resources, and multi-cloud resources
- Optimize combination of computing resources, RDMA high-speed network resources, and storage resources, and giving full play to the power of large-scale distributed clusters
- Support offline and online workload scheduling in global data centers integrating multi-cloud scenarios to achieve rational distributions

annually.