5 jobs for "Lead Machine Learning Engineer"

Responsibilities

The team is responsible for testing and evaluating global content security systems from an attacker's perspective, identifying potential vulnerabilities, and providing improvement recommendations, ensuring content safety across cultural and linguistic contexts.

Responsibilities
- Lead the development and continuous optimization of risk assessment frameworks, workflows, and SOPs across online signal detection, external escalations, and intelligence-driven investigations, ensuring standardized review processes and quality governance.
- Drive the evolution of the Red Team Risk Taxonomy and proactive risk forecasting capabilities, monitoring emerging regulatory trends, new technologies, AIGC ecosystems, and cross-platform threat vectors to identify risks before they materialize.
- Conduct proactive threat hunting and in-depth risk investigations by analyzing diverse risk signals, including enforcement gaps, external escalations, public sentiment, and abuse intelligence, delivering actionable risk assessment reports.
- Own the design and enhancement of AI-powered risk assessment workflows, including agent capability definition, prompt engineering, Human-in-the-Loop frameworks, and collaboration with engineering and machine learning teams to advance the Agentic Risk Assessment Platform.
- Build and manage external threat intelligence partnerships with security vendors, white-hat communities, industry peers, and intelligence providers to strengthen visibility into emerging threats, cybercrime trends, and abuse ecosystems.
- Partner cross-functionally with Product, Policy, Data Science, Trust & Safety, and Operations teams to translate risk findings into scalable mitigation solutions, enabling effective vulnerability management, evaluation frameworks, and closed-loop risk governance.

Qualifications

Minimum Qualification(s)
- Bachelor's degree or above in Computer Science, Information Security, Risk Management, or a related field.
- Proven experience in at least one of the following areas: Trust & Safety risk assessment, investigations, or policy enforcement, Content moderation strategy or risk control strategy, Online abuse mitigation, adversarial analysis, or enforcement gap/root-cause investigations, Cyber Threat Intelligence (CTI), red teaming, blue teaming, penetration testing, or cybersecurity operations
- Strong understanding of the capabilities and limitations of Large Language Models (LLMs) and multimodal AI systems, with hands-on experience in prompt design, human-in-the-loop workflows, and collaboration with engineering and machine learning teams to develop AI agent workflows.
- Strong analytical and data-driven problem-solving skills, with proficiency in SQL and Python. Experience building investigation dashboards, measuring key risk metrics (e.g., enforcement miss rates, pattern coverage), and conducting root-cause analysis based on large-scale online data.
- Proficiency in Chinese is required to communicate with internal stakeholders based in China.

Preferred Qualification(s)
- Experience in assessing and investigating multimodal and AIGC-related risks, including AI-generated images, deepfakes, synthetic audio/video content, and AI-enabled policy violations. Ability to analyze adversarial techniques, identify abuse patterns, and develop scalable risk detection methodologies.
- Experience working in fast-paced Trust & Safety, cybersecurity, risk management, or AI governance environments, with a strong interest in emerging online threats and evolving abuse ecosystems.

Responsibilities

Qualifications

Qualifications

Minimum Qualification(s)
- Bachelor's degree or above in Computer Science, Information Security, Risk Management, or a related field.
- Proven experience in at least one of the following areas: Trust & Safety risk assessment, investigations, or policy enforcement, Content moderation strategy or risk control strategy, Online abuse mitigation, adversarial analysis, or enforcement gap/root-cause investigations, Cyber Threat Intelligence (CTI), red teaming, blue teaming, penetration testing, or cybersecurity operations
- Strong understanding of the capabilities and limitations of Large Language Models (LLMs) and multimodal AI systems, with hands-on experience in prompt design, human-in-the-loop workflows, and collaboration with engineering and machine learning teams to develop AI agent workflows.
- Strong analytical and data-driven problem-solving skills, with proficiency in SQL and Python. Experience building investigation dashboards, measuring key risk metrics (e.g., enforcement miss rates, pattern coverage), and conducting root-cause analysis based on large-scale online data.
- Proficiency in Chinese is required to communicate with internal stakeholders based in China.

Preferred Qualification(s)
- Experience in assessing and investigating multimodal and AIGC-related risks, including AI-generated images, deepfakes, synthetic audio/video content, and AI-enabled policy violations. Ability to analyze adversarial techniques, identify abuse patterns, and develop scalable risk detection methodologies.
- Experience working in fast-paced Trust & Safety, cybersecurity, risk management, or AI governance environments, with a strong interest in emerging online threats and evolving abuse ecosystems.

About TikTok

TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.

Size: 5,001 - 10,000 employees
Industry: Entertainment & Gaming

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