Tech Lead-Machine Learning Engineer (Agent & Multi-Agent Systems) – AIGC Risk Intelligence
TikTok · Seattle, Washington, US
Our team is building the next generation of AI-native risk intelligence systems to address emerging challenges driven by large-scale AIGC content production....
Job description
Our team is building the next generation of AI-native risk intelligence systems to address emerging challenges driven by large-scale AIGC content production. As content creation becomes automated and adversaries adopt systematic experimentation (e.g., large-scale template variation and rapid iteration), traditional rule-based and single-model approaches are no longer sufficient. We are transitioning from monolithic LLM applications to a structured multi-agent architecture that emphasizes: Tool-augmented reasoning (ReAct-style systems) Modular skill composition: Execution traceability and observability: Feedback-driven system evolution: Cross-domain risk reasoning: We are seeking an experienced technical leader to define and implement this architecture. Responsibilities: Design structured agent workflows (e.g., Evaluate → Validate → Reflect → Summarize) Implement ReAct-style tool allocation and reasoning frameworks Develop short-term and long-term memory architectures Ensure robustness under adversarial and evolving conditions Design orchestration layers for coordinating vertical domain agents Build modular Skill systems for extensibility and reuse Define execution graph standards a...