Job Responsibilities:
1. Distributed Training Engineering Participate in the implementation of large-scale distributed training solutions. Lead the engineering deployment of data parallelism, model parallelism (TP/PP), and ZeRO optimization. Continuously tune GPU compute utilization and ensure stability of ultra-large-scale training tasks. 2. Compute Scheduling Optimization Deeply involved in the development and optimization of AI task scheduling logic. Implement fine-grained resource management, fault self-healing, and efficient Checkpoint mechanisms. Solve compute bottlenecks in complex gaming scenarios. 3. End-to-End Model Engineering Own the full pipeline from model training to inference deployment. Participate in operator performance profiling, model quantization, and high-performance inference pipeline construction. Support rapid iteration of AI in gaming business. 4. AI-Driven Engineering Evolution Actively adopt AI Coding technologies to improve development efficiency. Drive...