Big Data Engineer Intern (TikTok Recommendation Architecture) - 2027 Start

Responsibilities

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 us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth.
Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.
Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted.
Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.
Successful candidates must be able to commit to at least 3 months long internship period.

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
- Troubleshoot production systems, design and implement supporting mechanisms and tools to maintain overall production system stability
- 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 analyze information from large structured and unstructured datasets

Qualifications

Minimum Qualifications:
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline
- Familiarity with big data frameworks including Hadoop, Hive, Flink, Spark, Kafka, HBase, or Redis
- Proficiency in Java or C++ programming, with strong coding and troubleshooting abilities

Preferred Qualifications:
- Experience with data warehouse construction or large-scale data processing systems
- Strong sense of ownership and ability to work independently in fast-paced environments
- Good team collaboration skills and cross-cultural communication abilities

Responsibilities

Responsibilities

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 us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth.
Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.
Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted.
Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.
Successful candidates must be able to commit to at least 3 months long internship period.

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
- Troubleshoot production systems, design and implement supporting mechanisms and tools to maintain overall production system stability
- 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 analyze information from large structured and unstructured datasets

Qualifications

Qualifications

Minimum Qualifications:
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline
- Familiarity with big data frameworks including Hadoop, Hive, Flink, Spark, Kafka, HBase, or Redis
- Proficiency in Java or C++ programming, with strong coding and troubleshooting abilities

Preferred Qualifications:
- Experience with data warehouse construction or large-scale data processing systems
- Strong sense of ownership and ability to work independently in fast-paced environments
- Good team collaboration skills and cross-cultural communication abilities