Team Introduction： Our Recommendation Architecture Team is responsible for building and optimizing the architecture of the recommendation system to provide the most stable and best experience for users. The team focuses on optimizing the recommendation system architecture, ensuring stability and high availability, and improving the performance of both online services and offline data flows. Collaborating with the algorithm team, we work to enhance recommendation effectiveness and user experience, boost system performance while reducing costs, build data and service mid-platforms, and realize flexible and scalable high-performance storage and computing systems. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
- Design and implement offline data architectures for large-scale recommendation systems.
- Build flexible, scalable, and high-performance storage and computing systems.
- Ensure production system stability through troubleshooting and tooling development.
- Develop data analytics and visualization capabilities to transform raw data into meaningful insights.
- Apply data mining, machine learning, and NLP to extract insights from large-scale datasets.
Minimum Qualifications:
- Individuals who are completing or have recently completed a Bachelor's or Master's degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline.
- Familiar with many open source frameworks in the field of big data, e.g.Hadoop, Hive,Flink, FlinkSQL,Spark, Kafka, HBase, Redis, RocksDB, ElasticSearch etc.
- Familiar with Java, C ++ and other programming languages
- Strong coding and trouble shooting ability
Preferred Qualifications:
- Agile, quick self learner, highly self-motivated with strong sense of product ownership and creative problem solver.
- Good collaborator and team player, comfortable working in a fast moving, culturally diverse and globally distributed team environment.