Big Data Engineer, TikTok Ecommerce Recommendation Infrastructure
Sep 20, 2023 Singapore
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 10,000+ employees
- Industry: Technology: Consumer Internet
Why you should apply for a job to TikTok:
4.5/5 in overall job satisfaction
4.5/5 in supportive management
100% say women are treated fairly and equally to men
100% would recommend this company to other women
100% say the CEO supports gender diversity
Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›
Responsibilities
About the Team
E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-ecommerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the most stable and best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques.
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.
Responsibilities
- Design and implement a reasonable offline data architecture for large-scale recommendation systems
- Design and implement flexible, scalable, stable 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 modelling, 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 dynamic data reports as well
Qualifications
Minimum Qualifications
- Bachelor's degree or above in computer science, software engineering, or a related field
- 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
About the Team
E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-ecommerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the most stable and best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques.
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.
Responsibilities
- Design and implement a reasonable offline data architecture for large-scale recommendation systems
- Design and implement flexible, scalable, stable 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 modelling, 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 dynamic data reports as well
Minimum Qualifications
- Bachelor's degree or above in computer science, software engineering, or a related field
- 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
About the Team
E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-ecommerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the most stable and best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques.
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.
Responsibilities
- Design and implement a reasonable offline data architecture for large-scale recommendation systems
- Design and implement flexible, scalable, stable 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 modelling, 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 dynamic data reports as well
Qualifications
Minimum Qualifications
- Bachelor's degree or above in computer science, software engineering, or a related field
- 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
Responsibilities
ResponsibilitiesAbout the Team
E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-ecommerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the most stable and best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques.
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.
Responsibilities
- Design and implement a reasonable offline data architecture for large-scale recommendation systems
- Design and implement flexible, scalable, stable 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 modelling, 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 dynamic data reports as well
Qualifications
QualificationsMinimum Qualifications
- Bachelor's degree or above in computer science, software engineering, or a related field
- 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
Additional Information
- Posted: Sep 20, 2023