<p>Leveraging substantial data and computing resources and through continued investment in these domains, we have developed a proprietary general-purpose model with multimodal capabilities. In the Chinese market, Doubao models power over 50 ByteDance apps and business lines, including Doubao, Coze, and Dreamina, and is available to external enterprise clients via Volcano Engine. Today, the Doubao app stands as the most widely used AIGC application in China.</p> <p>The Machine Learning (ML) System sub-team combines system engineering and the art of machine learning to develop and maintain massively distributed ML training and Inference system/services around the world, providing high-performance, highly reliable, scalable systems for LLM/AIGC/AGI. In our team, you'll have the opportunity to build the large-scale heterogeneous system integrating with GPU/NPU/RDMA/Storage and keep it running stable and reliable, enrich your expertise in coding, performance analysis and distributed system, and be involved in the decision-making process. You'll also be part of a global team with members from the United States, China and Singapore working collaboratively towards unified project direction.</p> <p>Responsibilities:</p> <ol> <li>Responsible for the design and development of resource scheduling, including model training, model evaluation and model inference in various scenarios (LLM/AIGC/CV/Speech, etc.) </li><li>Responsible for the optimal 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 </li><li>Responsible for the optimal combination of computing resources, RDMA high-speed network resources, and storage resources, and giving full play to the power of large-scale distributed clusters </li><li>Responsible for offline and online workload scheduling in global data centers integrating multi-cloud scenarios to achieve rational distributions </li></ol>