ML Engineer Intern — Trust & Safety (PhD Candidate)

TikTok; Singapore; On-site; SGD 17,000 - 28,000; Full time

Job summary

TikTok is seeking a Machine Learning Engineer Intern (Trust & Safety) for a 2026 start date in Singapore. The role targets PhD students who will build safety systems, work on scalable classifiers and collaborate with cross-functional teams to protect the platform.

The internship emphasizes applying ML, NLP, and CV techniques to improve trust and safety, with industry-leading research opportunities and exposure to real-world content moderation challenges.

Qualifications

• Currently pursuing a PhD in Computer Science, engineering or quantitative field.
• Solid experience in machine learning, pattern recognition, NLP, data mining, or computer vision.
• Experience in recommendation, search, advertising, or related projects.
• Publications in top AI conferences or journals (KDD, IJCAI, WWW, WSDM, ICML, NeurIPS, CVPR, ECCV, ICCV, ACL, etc) is a plus.
• Good understanding of data structures and algorithms.
• Passion for techniques and solving challenging problems.

Responsibilities

• Build industry-leading content safety systems for TikTok.
• Develop highly-scalable classifiers, tools, models and algorithms leveraging cutting-edge machine learning, computer vision and data mining technologies.
• Understand product objectives and improve trust and safety strategy and model's performance.
• Work with cross-functional teams to protect TikTok globally.

Skills

Machine learning

NLP

Data mining

Computer vision

Pattern recognition

Education

PhD in Computer Science/Engineering/Quantitative field

Job description

TikTok is seeking a Machine Learning Engineer Intern (Trust & Safety) for a 2026 start date in Singapore. The role targets PhD students who will build safety systems, work on scalable classifiers and collaborate with cross-functional teams to protect the platform.

The internship emphasizes applying ML, NLP, and CV techniques to improve trust and safety, with industry-leading research opportunities and exposure to real-world content moderation challenges.