Software Engineer Intern (Trust & Safety Algorithm Engineering) - 2026 Start (BS/MS)

sibilities:

• Work closely with business teams to optimize the integration plan for algorithm applications, improve efficiency in evaluating and using algorithm applications across various business scenarios, and reduce the cost of managing and optimizing algorithm applications in different business scenarios.
• Be responsible for the architectural design, development, and performance tuning of algorithm applications, solving technical challenges such as high concurrency, high reliability, and high scalability. Work includes multiple sub-areas: ML model training and evaluation, model optimization, model inference, model management, dataset management, workflow orchestration, etc.
• Responsible for the design and development of Machine Learning infrastructure for LLM/AIGC, etc
• Be responsible for researching and implementing cutting-edge engineering technologies related to LLM, NLP, CV.

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.

Successful candidates must be able to commit to either of the following Internships

• From January to June
• From May to August (Summer)

Qualifications

Minimum Qualifications:

• Undergraduate or Postgraduate currently pursuing computer science or a related technical discipline.
• Familiar with one or two programming languages, such as C++, Go, or Python, and knowledgeable about CUDA or deep learning frameworks (such as PyTorch, Deepspeed, Megatron, vllm, etc.).
• Understanding of the principles of distributed systems, large-scale data processing, and parallel computing
• Interested and experienced in one or more of the following areas: machine learning, deep learning, computational acceleration, and performance optimization.

Preferred Qualification:

• Familiar with the ML Infrastructure of Large Model training and inference

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 [email protected]