ML Engineer - Risk & Safety (Fraud & Multimodal AI)

TikTok Pte. Ltd.

Singapore

On-site

SGD 150,000 - 210,000

Full time

43 hours ago

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Job summary

TikTok Pte. Ltd. seeks a senior AI/ML leader in Singapore to join the BRIC team. You will design and implement risk control algorithms and systems across TikTok Drama, TikTok AI, and Open Platform, focusing on AI abuse, advertising fraud, and traffic integrity.

Collaborating with engineering, product, advertising, and data teams, you will develop real-time risk detections, evaluate PoCs, and drive scalable production solutions while advancing AI safety and platform integrity.

Qualifications

Master's degree or higher in Computer Science, AI, Statistics, or related field.
Strong ML/DL theory with experience in classification, ranking, sequence modeling, anomaly detection (XGBoost, DeepFM, Transformers, GNNs).
Strong programming skills in Python, C++, or Go with PyTorch or TensorFlow experience.
Analytical thinking, data intuition, and passion for adversarial risk control.

Responsibilities

End-to-end Risk System Development: Lead the design and development of risk control algorithms and systems across TikTok Drama, TikTok AI, TikTok Open Platform, and other emerging businesses, focusing on detecting and mitigating AI capability abuse, advertising fraud, fake conversions, traffic and engagement manipulation, account farming, account hijacking, and API abuse.
Multimodal Risk Model Development & Optimization: Develop high-precision, low-latency, and reliable real-time risk detection and scoring models using large-scale multimodal data.
Adversarial Defense & Risk Discovery: Analyze sophisticated abuse patterns, identify emerging threats through data analysis and risk mining, and develop robust adversarial strategies and hybrid rule-model defense systems.
Cutting-edge Research & Implementation: As a technical owner, drive technology research, solution evaluation, architecture design, PoC validation, and production implementation.
Explore and apply advanced technologies, including Agentic AI, LLM post-training and fine-tuning, multimodal representation learning, behavioral sequence modeling, and graph learning, to enable automated risk discovery, investigation, reasoning, and decision-making.
Cross-functional Collaboration: Own the full lifecycle of algorithm development, from technical architecture and model evaluation to deployment and continuous optimization.
Collaborate with engineering, product, advertising, growth, strategy, moderation, and data teams to drive technical innovation and establish scalable, reusable risk control capabilities across emerging business scenarios.