Team Introduction: Our Live Recommendation Architecture Team is responsible for building up and optimizing the architecture for live broadcast recommendation system to provide the most stable and best experience for our users. The team is responsible for system stability and high availability, online services and offline data flow performance optimization, solving system bottlenecks, reducing cost overhead, building data and service mid-platform, realizing flexible and scalable high-performance storage and computing systems. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques. 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 reasonable offline data architecture for large-scale recommendation systems
- Design and implement flexible, scalable, and high-performance storage and computing systems
- Trouble-shooting of the production system, design and implement the necessary mechanisms and tools to ensure the stability of the overall operation of the production system
- Build industry-leading distributed systems such as storage and computing to provide reliable infrastructure for massive data and large-scale business systems
- Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software
- Apply data mining, data modeling, natural language processing, and machine learning to extract and analyse information from large structured and unstructured datasets
- Visualise, interpret, and report data findings and may create data reports as well
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