Model Infra Engineer Intern (TikTok Recommendation Architecture) - 2026 Start (BS/MS)

Responsibilities

Team Introduction
The Recommendation Architecture team is responsible for building up and optimizing our recommendation system's architecture to provide the most stable and best experience for our users. We are looking for highly motivated Interns who are passionate about optimizing Large Language Models (LLMs) and large-scale recommendation models.

We are looking for talented individuals to join us for an internship in from Sept. 2025 onwards. Internships at TikTok aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at TikTok.

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.
Successful candidates must be able to commit to at least 3 months long internship period.

Responsibilities
- Optimize model performance and memory efficiency on GPU-based systems.
- Collaborate with research and infra teams to deploy high-throughput training and inference pipelines.
- Develop tools and libraries to accelerate deep learning workloads at scale.
- Analyze system performance (e.g. GPU profiling, kernel analysis, throughput tuning).

Qualifications

Minimum Qualifications:
- Undergraduate, or Postgraduate who is currently pursuing a degree/master in Computer Science, EE, or related field.
- Familiarity with deep learning and frameworks like PyTorch or TensorFlow. And understanding of GPU basics (memory hierarchy, compute kernels).
- Programming experience in Python/C++/CUDA/Trition is a plus.

Preferred Qualifications:
- Course or project experience with LLMs or recommender systems.
- Exposure to CUDA, NCCL, or deep learning compiler stacks (e.g. XLA, TensorRT).
- Publications or open-source contributions are a bonus.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

If you have any questions, please reach out to us at apac-earlycareers@tiktok.com