Responsibilities and Tasks:
- Design, develop, and maintain backend systems and services supporting AI models, ensuring high performance, stability, and scalability.
- Integrate various machine learning models and algorithms into backend systems to solve business problems, such as recommendation systems, predictive analytics, etc.
- Optimize and adjust backend systems to improve the performance and efficiency of AI models.
- Design and implement APIs and microservices to make AI functionalities accessible via RESTful interfaces.
- Implement monitoring and logging to track the performance of backend systems and troubleshoot issues.
- Research and evaluate new AI technologies and tools to continuously improve the backend architecture.
- Responsible in writing clear documentation detailing the design, implementation, and usage of backend systems.
Position Requirements:
- Proficient in the Python programming language and familiar with Python's libraries and frameworks.
- Experience in backend development, understanding of database systems (such as SQL and NoSQL), as well as web development and API design.
- Good data handling and engineering skills, capable of managing large datasets.
- Able to effectively communicate and collaborate, working with cross-functional teams to solve problems.
- Problem-solving and innovative thinking skills, able to work in complex environments.
- Keen on the latest developments in the field of artificial intelligence, willing to continuously learn and adapt to new technologies.
- Bachelor’s degree or higher, preferably in Computer Science, Engineering, Mathematics, Statistics, or a related field.
- At least 2 years of experience in backend development or as an AI engineer.
- Bilingual, fluent in Chinese and English is a plus (as candidates need to liaise with Chinese/Mandarin speaking counterparts in China for job purposes)
Desirable Qualities:
- Strong communication skills, priority given to those with experience in text AI research and development.
- Familiar with big data processing technologies like Hadoop, Spark, Flink, Flume, Hive, and Airflow, able to effectively apply them in practical projects.
- In-depth understanding of configuring and managing AWS cloud platform, additional points for those with AWS certifications.
- Able to fluently read English documentation, quickly absorb and apply new knowledge and technology.
