Software Engineer, ML System Scheduling

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.

Responsibilities:
1. Responsible for the design and development of resource scheduling, including model training, model evaluation and model inference in various scenarios (LLM/AIGC/NLP/CV/Speech, etc.)
2. 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
3. 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
4. Responsible for offline and online workload scheduling in global data centers integrating multi-cloud scenarios to achieve rational distributions

The base salary range for this position in the selected city is $177688 - $341734 annually.