1. Responsible for inference optimization and development implementation of industry large model applications, including but not limited to model quantization, pruning, distillation, and engineering deployment. 2. Lead the development of large model business application platforms (AI middleware/large model projects), tackling key engineering challenges. 3. Collaborate with project teams to apply large models to real-world business scenarios.

1. Solid foundation in algorithms and data structures, proficient in programming languages such as Python and C++. Bonus: Winners of programming competitions like ACM/ICPC. 2. Familiar with mainstream large model architectures, training/inference workflows, acceleration methods, engineering development, and deployment techniques. 3. Strong technical passion, self-motivation, resilience, excellent logical thinking, and the ability to decompose and solve complex problems.