Software Engineer Graduate (TikTok Live Recommendation Architecture) - 2027 Start
Aug 3, 2026 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
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
- Build and maintain high-performance online services and data pipelines for TikTok Live recommendation systems.
- Design and develop high-performance computing frameworks and storage systems to support real-time live streaming scenarios.
- Build globalized large-scale recommendation systems for live broadcast use cases.
- Ensure production system stability through troubleshooting, mechanism design, and tooling development.
- Develop data analytics and visualization capabilities to transform raw data into actionable insights.
- Apply data mining, machine learning, and NLP techniques to extract insights from large-scale datasets.
Qualifications
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.
- Experience programming in at least one of the following programming languages: C, C++, Java or Golang
- Effective communication skills and a sense of ownership and drive
- 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. for big data roles.
- Familiar with Java, C ++ and other programming languages for big data roles.
- Strong coding and trouble shooting ability
Preferred Qualifications:
- Experienced in at least one area of the following areas: personalized recommendations, search engine, machine learning, distributed storage system, big data frameworks is a plus
- 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
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
- Build and maintain high-performance online services and data pipelines for TikTok Live recommendation systems.
- Design and develop high-performance computing frameworks and storage systems to support real-time live streaming scenarios.
- Build globalized large-scale recommendation systems for live broadcast use cases.
- Ensure production system stability through troubleshooting, mechanism design, and tooling development.
- Develop data analytics and visualization capabilities to transform raw data into actionable insights.
- Apply data mining, machine learning, and NLP techniques 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.
- Experience programming in at least one of the following programming languages: C, C++, Java or Golang
- Effective communication skills and a sense of ownership and drive
- 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. for big data roles.
- Familiar with Java, C ++ and other programming languages for big data roles.
- Strong coding and trouble shooting ability
Preferred Qualifications:
- Experienced in at least one area of the following areas: personalized recommendations, search engine, machine learning, distributed storage system, big data frameworks is a plus
- 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
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
- Build and maintain high-performance online services and data pipelines for TikTok Live recommendation systems.
- Design and develop high-performance computing frameworks and storage systems to support real-time live streaming scenarios.
- Build globalized large-scale recommendation systems for live broadcast use cases.
- Ensure production system stability through troubleshooting, mechanism design, and tooling development.
- Develop data analytics and visualization capabilities to transform raw data into actionable insights.
- Apply data mining, machine learning, and NLP techniques to extract insights from large-scale datasets.
Qualifications
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.
- Experience programming in at least one of the following programming languages: C, C++, Java or Golang
- Effective communication skills and a sense of ownership and drive
- 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. for big data roles.
- Familiar with Java, C ++ and other programming languages for big data roles.
- Strong coding and trouble shooting ability
Preferred Qualifications:
- Experienced in at least one area of the following areas: personalized recommendations, search engine, machine learning, distributed storage system, big data frameworks is a plus
- 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
Responsibilities
ResponsibilitiesTeam 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
- Build and maintain high-performance online services and data pipelines for TikTok Live recommendation systems.
- Design and develop high-performance computing frameworks and storage systems to support real-time live streaming scenarios.
- Build globalized large-scale recommendation systems for live broadcast use cases.
- Ensure production system stability through troubleshooting, mechanism design, and tooling development.
- Develop data analytics and visualization capabilities to transform raw data into actionable insights.
- Apply data mining, machine learning, and NLP techniques to extract insights from large-scale datasets.
Qualifications
QualificationsMinimum 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.
- Experience programming in at least one of the following programming languages: C, C++, Java or Golang
- Effective communication skills and a sense of ownership and drive
- 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. for big data roles.
- Familiar with Java, C ++ and other programming languages for big data roles.
- Strong coding and trouble shooting ability
Preferred Qualifications:
- Experienced in at least one area of the following areas: personalized recommendations, search engine, machine learning, distributed storage system, big data frameworks is a plus
- 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
Additional Information
- Posted: Aug 3, 2026