Team Introduction
Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation products to provide the most stable and best experience for ourTikTok users.
University graduates are important parts to our team with your fresh ideas and creative thoughts. We are looking for talented individuals to join our team in 2025.
As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities.
Co-create a future driven by your inspiration with TikTok. Successful candidates must be able to commit to an onboarding date by end of year 2025.
Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible. 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.
Online Assessment Candidates who pass resume evaluation will be invited to participate in TikTok's technical online assessment in HackerRank. Responsibilities :
- Build and maintain high performance online services for TikTok recommendation system to supportvarious types of products, such as For You Feed, E-commerce, Social, etc.
- Build extremely efficient and reliable data pipelines for candidates generation, profile generation, training examples generation, realtime online training, etc;
- Build globalized large-scale recommendation system;
- Design and develop high performance computing frameworks and storage systems.
Minimum Qualifications :
- Bachelor's degree or above, majoring in Computer Science, or related fields, expected to graduate and start in 2024;
- Experience in programming, included but not limited to, the following programming languages : C, C++, Java or Python;
- Effective communication skills, self-driven learner, a sense of ownership
- Projects or research 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.