Big Data Engineer Graduate (TikTok Application Computing, Data + AI) - 2026 Start (BS/MS)
Singapore, Singapore
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About The Team
TikTok's Recommendation Architecture Team is responsible for designing and developing the architecture and computing systems that power the recommendation engines behind products with over a billion users. The team ensures system stability and high availability, abstracts general-purpose real-time and batch computing frameworks, and builds flexible, scalable, high-performance storage systems and computing models. We provide core infrastructure and general-purpose components for key areas such as deduplication, counting, feature generation, training pipelines, and stream-batch computing engines, enabling the success of recommendation services at scale.
We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok.
Successful candidates must be able to commit to an onboarding date by end of year 2026. 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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
- Design and implement scalable distributed computing and training systems for large-scale recommendation systems.
- Build flexible, extensible, stable, and high-performance components for offline storage, computing, and training.
- Perform troubleshooting for production systems, and design and develop tools and mechanisms to ensure system stability and reliability.
- Develop industry-leading distributed training and computing frameworks for recommendation systems, providing robust infrastructure for massive datasets and large-scale business systems.
TikTok's Recommendation Architecture Team is responsible for designing and developing the architecture and computing systems that power the recommendation engines behind products with over a billion users. The team ensures system stability and high availability, abstracts general-purpose real-time and batch computing frameworks, and builds flexible, scalable, high-performance storage systems and computing models. We provide core infrastructure and general-purpose components for key areas such as deduplication, counting, feature generation, training pipelines, and stream-batch computing engines, enabling the success of recommendation services at scale.
We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok.
Successful candidates must be able to commit to an onboarding date by end of year 2026. 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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
- Design and implement scalable distributed computing and training systems for large-scale recommendation systems.
- Build flexible, extensible, stable, and high-performance components for offline storage, computing, and training.
- Perform troubleshooting for production systems, and design and develop tools and mechanisms to ensure system stability and reliability.
- Develop industry-leading distributed training and computing frameworks for recommendation systems, providing robust infrastructure for massive datasets and large-scale business systems.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
Big Data Jobs
Deep Learning Jobs
Engineering Jobs
Tags: Architecture Big Data Pipelines
Region:
Asia/Pacific
Country:
Singapore
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