PhD ML Engineer Intern — E‑Commerce Risk & AI Agents

TikTok; Singapore; On-site; SGD 22,000 - 39,000; Part time

Job summary

TikTok is offering a PhD internship as Machine Learning Engineer Intern (Global E-Commerce, Risk Control) starting 2027. The role focuses on building ML models to detect fraud across the ecommerce ecosystem and collaborating with cross-functional teams.

Responsibilities include developing domain-specific ML/LLMs, analyzing large-scale security data, and productionizing AI pipelines for real-time prevention, with deployment and monitoring support from software platforms.

Qualifications

• Currently pursuing a PhD in Computer Science or related fields.
• Responsible for development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
• Good coding skills in one or more programming language.

Responsibilities

• Develop domain-specific machine learning / LLMs / Agents to decode and prevent intricate, cross-domain fraudulent activities.
• Analyze massive business and security data to mine abnormal user behavior, and uncover evolving risky patterns.
• Productionize AI agent pipelines engineered for real-time prevention under massive global traffic.
• Analyze / test the effectiveness of the built solutions.
• Work in a cross-functional team setting to mitigate business risks.
• Work with relevant software platform to develop/deploy/monitor the models.

Skills

Deep learning

Operations research

Python

MLmodeling

Education

PhD in Computer Science or related fields

Tools

PyTorch

Scikit-learn

LangChain

Hugging Face Transformers

Job description

TikTok is offering a PhD internship as Machine Learning Engineer Intern (Global E-Commerce, Risk Control) starting 2027. The role focuses on building ML models to detect fraud across the ecommerce ecosystem and collaborating with cross-functional teams.

Responsibilities include developing domain-specific ML/LLMs, analyzing large-scale security data, and productionizing AI pipelines for real-time prevention, with deployment and monitoring support from software platforms.