About The Team
The mission of our AML team is to push the next-generation AI infrastructure and recommendation platform for the ads ranking, search ranking, live & e-Commerce ranking in our company. We also drive substantial impact on core businesses of the company.

Responsibilities
- Responsible for the overall architecture design and implementation of model inference services, building a high-performance, highly available, and scalable enterprise-level inference system for large-parameter, high-complexity AI models, overcoming various architectural challenges in the implementation of complex model inference, and supporting the efficient launch of models across all business scenarios.
- Responsible for the R&D and optimization of the core modules of the inference framework, covering core capabilities such as inference engine scheduling, monitoring and alerting, canary release, etc., continuously iterating on the framework performance, and resolving performance bottlenecks, resource bottlenecks, and stability issues in high-concurrency and large-model inference scenarios.
- Keep track of the latest inference technologies in the industry, conduct technology selection and innovation in combination with business scenarios, accumulate distributed high-concurrency service architecture solutions, and promote the upgrade and standardization of the team's technical system.

Minimum Qualification(s)
- Bachelor’s degree in Computer Science or equivalent with at least 1 year of relevant experience
- Familiar with basic Linux commands, with solid C/C++ programming skills and knowledge of data structures and algorithms.
- Familiar with the basic principles of multi-threaded concurrency, proficient in basic usages such as thread usage, synchronization locks, and thread pools, able to identify common concurrency issues, and possess the ability to perform basic performance tuning in multi-threaded scenarios.
- Excellent programming skills, solid understanding of basic data structures, proficient in Python, and familiar with C++.
- Have experience in R&D projects of high-concurrency distributed services, and be familiar with service latency and resource optimization.

Preferred Qualification(s)
- Have practical project experience and understanding of source code in high-concurrency services/frameworks such as Redis, RocksDB, BRPC, GRPC, etc.
- Understand the operating mechanism of GPUs, and have relevant project experience and optimization capabilities in GPU service resource management and control.