Tech Lead Machine Learning Engineer - Multimodal/LLM, Trust and Safety

Responsibilities

We are the Trust & Safety Algorithms Team at TikTok, dedicated to building intelligent systems that safeguard our content ecosystem and protect our global community. Our team develops advanced machine learning solutions to moderate content across multiple modalities - including video, images, text, and audio - in alignment with our Community Guidelines.

We play a critical role in detecting and preventing harmful content, mitigating platform abuse, and maintaining a safe, trustworthy environment for users around the world.

Content moderation represents one of the most impactful and technically complex applications of large-scale machine learning. It is also a frontier domain for Large Language Models (LLMs) and multimodal foundation models. By joining our team, you will work at the cutting edge of ML innovation, tackle highly challenging real-world safety problems, and drive meaningful societal impact at global scale.
Responsibilities:
- Own the design and delivery of a core system module within a key content safety vertical
- Lead ML engineers to deliver high-quality, production-ready solutions with strong technical rigor.
- Architect and implement end-to-end ML pipelines, including data processing, model training, evaluation, deployment, and monitoring.
- Apply advanced CV/NLP/LLM techniques to solve real-world moderation challenges across video, image, text, and audio.
- Continuously improve model performance through data analysis, error diagnosis, feature engineering, and model innovation.
- Collaborate closely with cross-functional partners (product, policy, operations etc.) to ensure technical solutions align with evolving business and safety requirements.

Qualifications

Minimum Qualifications:
- Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field. 4+ years of hands-on experience in machine learning system development.
- Proven experience leading small technical teams or driving major ML modules end-to-end.
- Experience deploying large-scale ML models into production environments.
- Strong expertise in at least one of the following areas: Computer Vision, Natural Language Processing, Large Language Models / Generative AI and Multimodal modeling
- Solid understanding of model training, fine-tuning, evaluation, and optimization; experience with LLM alignment, safety modeling, or trust & safety domains is a strong plus.
- Strong ownership mindset - able to independently drive ambiguous problems to clear technical solutions.
- Hands-on technical leader who can both design architecture and dive into implementation details.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $254400 - $588000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

Responsibilities

Responsibilities

We are the Trust & Safety Algorithms Team at TikTok, dedicated to building intelligent systems that safeguard our content ecosystem and protect our global community. Our team develops advanced machine learning solutions to moderate content across multiple modalities - including video, images, text, and audio - in alignment with our Community Guidelines.

We play a critical role in detecting and preventing harmful content, mitigating platform abuse, and maintaining a safe, trustworthy environment for users around the world.

Content moderation represents one of the most impactful and technically complex applications of large-scale machine learning. It is also a frontier domain for Large Language Models (LLMs) and multimodal foundation models. By joining our team, you will work at the cutting edge of ML innovation, tackle highly challenging real-world safety problems, and drive meaningful societal impact at global scale.
Responsibilities:
- Own the design and delivery of a core system module within a key content safety vertical
- Lead ML engineers to deliver high-quality, production-ready solutions with strong technical rigor.
- Architect and implement end-to-end ML pipelines, including data processing, model training, evaluation, deployment, and monitoring.
- Apply advanced CV/NLP/LLM techniques to solve real-world moderation challenges across video, image, text, and audio.
- Continuously improve model performance through data analysis, error diagnosis, feature engineering, and model innovation.
- Collaborate closely with cross-functional partners (product, policy, operations etc.) to ensure technical solutions align with evolving business and safety requirements.

Qualifications

Qualifications

Minimum Qualifications:
- Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field. 4+ years of hands-on experience in machine learning system development.
- Proven experience leading small technical teams or driving major ML modules end-to-end.
- Experience deploying large-scale ML models into production environments.
- Strong expertise in at least one of the following areas: Computer Vision, Natural Language Processing, Large Language Models / Generative AI and Multimodal modeling
- Solid understanding of model training, fine-tuning, evaluation, and optimization; experience with LLM alignment, safety modeling, or trust & safety domains is a strong plus.
- Strong ownership mindset - able to independently drive ambiguous problems to clear technical solutions.
- Hands-on technical leader who can both design architecture and dive into implementation details.