The role
From TikTok's own posting.
About the Team
Our Search Engineering Team builds and owns TikTok's search engine, combining information retrieval with modern machine learning from NLP, CV, and recommender systems. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.
The Data Infrastructure team owns the data layer: how billions of videos and articles are ingested and indexed, how features are computed and served, how petabytes of user actions and features become training data, and how long sequences are modeled. Every retrieval and ranking model in TikTok Search runs on data our systems produce.
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 own query/video pipelines — ingestion, enrichment, and streaming/batch index construction at billion-doc scale with near-real-time freshness.
- Develop the feature engineering platform: computation, backfill, storage, and serving, with strong online/offline consistency guarantees.
- Build streaming and batch sample pipelines that turn user actions and features into high-quality training data.
- Improve data quality, observability, and cost efficiency across PB-scale storage and compute.
Minimum Qualification(s)
- Currently pursuing a Bachelor's degree in Computer Science or a related technical discipline.
- Strong programming skills in Java, C++, or Python.
- Production experience with data frameworks such as Spark, Flink, or Hive/Iceberg.
- Solid distributed systems fundamentals, and the ability to debug and optimize complex systems in production.
Preferred Qualification(s)
- Currently pursuing a Master's degree in Computer Science or a related technical discipline.
- Experience with search, recommendation, or ads data infrastructure.
- Experience with feature stores and training sample pipelines.
- Familiarity with real-time indexing, inverted index, or embedding/vector retrieval pipelines.
- Experience using AI coding assistants and agents to improve day-to-day development productivity.