Machine Learning Engineer - Emerging Business - TikTok BRIC

Responsibilities

Business Risk Integrated Control (BRIC) is a global team protecting ByteDance users, platform health, and the authenticity of community and business ecosystems. We build the risk control algorithms, AI technologies, platforms, and infrastructure behind that work, across products including TikTok, CapCut, Lemon8, and Lark.

Our work spans account and content integrity, and safety across advertising and e-commerce. We apply machine learning across areas such as graph learning, anomaly detection, and multimodal models to understand users, content, behavior, and the relationships between them. The challenge is recognizing genuine activity accurately, so the people using our products never notice the systems working.

You will shape the trust, safety, and sustainable growth of ByteDance's global platforms, applying advanced AI to some of the hardest real-world problems in the field.

TikTok's Emerging Businesses encompass fast-growing products and innovative business models, including TikTok Drama, TikTok AI, and TikTok Open Platform, spanning content creation, AI capabilities, open ecosystems, and monetization opportunities. Operating in complex global regulatory and highly adversarial environments, the team focuses on critical risks such as AI feature and model capability abuse, advertising fraud and fake conversions, traffic and engagement manipulation, large-scale account farming, and account abuse.

Our mission is to build scalable and intelligent risk control systems across AI safety, advertising anti-fraud, traffic integrity, account security, and platform capability protection, safeguarding sustainable business growth, maintaining a trustworthy commercial ecosystem, and ensuring the secure and compliant use of platform resources.

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, including account attributes, device fingerprints, content signals, AI feature usage logs, advertising conversion funnels, user behavior sequences, and API invocation logs.
- 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 to protect emerging businesses against evolving attacks.
- Cutting-edge Research & Implementation: As a technical owner, drive technology research, solution evaluation, architecture design, proof-of-concept (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.

Qualifications

Minimum Qualification(s)
- Master's degree or higher in Computer Science, Mathematics, Statistics, Artificial Intelligence, or a related field.