TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul, and Tokyo.

Why Join Us
At TikTok, our people are humble, intelligent, compassionate and creative. We create to inspire - for you, for us, and for more than 1 billion users on our platform. We lead with curiosity and aim for the highest, never shying away from taking calculated risks and embracing ambiguity as it comes. Here, the opportunities are limitless for those who dare to pursue bold ideas that exist just beyond the boundary of possibility. Join us and make impact happen with a career at TikTok.

Our Business Integrity team has a strong user focus and a dedication to technical excellence. We aim to meet our users’ needs with reliable and high-performing platforms and services. We are looking for strong machine learning engineers who are excited to grow their business understanding, build highly scalable machine learning models, and partner across disciplines with global teams, in pursuit of excellence. Given the fast growth of TikTok in the world, we are working on building a next-generation content understanding system for TikTok monetization. We are seeking machine learning engineers at all levels experienced in machine learning, which can help us create an ecosystem that rewards high quality user experience and advertiser value.

Responsibilities:
1. Be responsible for content understanding of commercial products, such as ads, e-commerce, short video, and live streaming.
2. Be responsible for data mining, feature engineering, and building scalable machine learning models to establish monetization ecology.
3. Optimize computational efficiency and improve stability of machine learning models to deal with billion scale business data.
4. Based on business data, explore and implement various cutting-edge technologies, such as pre-training, self-supervised learning, few-shot learning, etc.
5. Explore state-of-the-art AIGC techniques and build a new generation of AIGC-based monetization ecology systems.