Tech Lead Machine Learning Engineer - Multimodal/LLM, Trust and Safety
TikTok · Singapore ·
- Work mode
- Onsite
- Seniority
- Lead
- Category
- ML ai
- Experience
- 4+ years
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.
Minimum Qualification(s):
- 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.
- 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.
Preferred Qualification(s):
- Experience with LLM alignment, safety modeling, or trust & safety domains.