TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us
Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.

TikTok's advertising business is built on leveraging external signals to create features and labels that train personalized ad models. As signal loss becomes a growing challenge in online advertising, our Ads Identity and Attribution team is at the forefront of addressing this shift. We focus on identity matching (deriving user identification from signals) and ad attribution (assigning signals to ad touchpoints), both critical to the data foundation of TikTok's ad delivery system. What began as a technical engineering problem has evolved into a large-scale system challenge, requiring both cutting-edge data processing technologies and innovative machine learning algorithms.

Responsibilities:
By joining us, you'll have the opportunity to participate in the development of algorithms and systems for one of the world's leading ranking and recommendation services. Your work will mainly include:
1. Developing advanced ML and LLM algorithms (including retrieval, ranking, calibration modules) for signal matching systems at the scale of millions of QPS
2. Iterating and optimizing ranking algorithms and strategies through data analysis and experimentation.
3. Leading the development and operational work of large-scale, distributed real-time systems for testing, integrating, and deploying machine learning models.
4. Creating algorithms and data-driven solutions that utilize one of the world’s richest user behavior datasets for various ads-related use cases, such as ads ranking, targeting, bidding, calibration, and reporting.
5. Collaborating with product teams to define product strategies and features.