About The Team The Applied Machine Learning (AML) team combines system engineering and the art of machine learning to develop and run massively distributed recommendation systems around the world.
In the team, you'll have the opportunity to sharpen your expertise in coding, performance analysis and large system operation, and get heavily involved in the process of hardware/capacity decision-making.
The efficiency tools team provides a high-quality tool platform and technical outputs for the efficiency and training of online models and the management of the team's massive hardware resources.
Responsibilities:
- Research, design, and develop computer and network software or specialised utility programs.
- Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis.
- Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures.
- Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements.
- Research, design, and develop computer and network software or specialised utility programs.
- Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis.
- Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures.
Requirements
Minimum Qualifications:
- Proficient in at least one of Python/Golang/C++, with solid coding skills and good coding practices.
- Proficient in using common storage and middleware systems such as MySQL, Redis, and MQ, with basic troubleshooting and performance tuning capabilities.
- Familiar with Python frameworks and libraries such as Flask, Celery, Django, Tornado, NumPy; or familiar with common Go open-source frameworks such as Beego, Gin, Gorm, Sarama, and gRPC-Go.
- Understand and have experience with common time-series/data components such as OpenTSDB, Prometheus, InfluxDB, and OLAP databases like ClickHouse.
- Strong sense of responsibility, good learning ability, communication skills, and self-motivation, with solid team collaboration.
- Good documentation habits, able to write and update workflow and technical documents in a timely manner as required.
Preferred Qualifications:
- Experience in upper-layer business systems such as search systems or recommendation systems (development or operations) is a plus.
- Experience with the React framework and its ecosystem; familiarity with visualization stacks such as ECharts, AntV, and D3.js is preferred.
- Hands-on experience with AI Agent development is preferred.
- Familiarity with cloud computing concepts, including virtual machines and containers; a solid understanding of networking and message queues is a plus.
- Experience building CPU/GPU resource management platforms; familiarity with common NVIDIA GPU architectures; and experience with anomaly diagnosis and troubleshooting is preferred.
- Experience with distributed storage systems such as HDFS and key-value stores like LevelDB/RocksDB is preferred.