Machine Learning Engineer, Search (NLP) - Singapore

About TikTok
TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require TikTok sponsorship of a visa.

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

About the team
The Search team is mainly responsible for the search algorithm innovation and architecture research and development of Douyin, international short video, Jinri Toutiao, Watermelon video and other products, as well as e-commerce, life services and other businesses. We use cutting-edge machine learning technology for end-to-end modeling and continuous innovation and breakthroughs, while focusing on the construction and performance optimization of distributed systems and machine learning systems.

Department work:
1. Participate in the research and development of international short video search engines, using cutting-edge machine learning algorithms and massive data to make the most exciting technologies and give users the best search experience;
2. Participate in the improvement of international short video search algorithms. Optional directions include:
(1) Explore cutting-edge NLP technologies: from basic word segmentation, NER, to application-based Query analysis, basic correlation, etc., full-link application of deep learning models, every detail is full of challenges;
(3) Cross-modal matching technology: Apply CV + NLP deep learning technology in search to make search have more powerful retrieval capabilities in the above businesses. Engage in the research and development of video search, visual search and other related algorithms, including video content understanding, visual representation learning, multi-modal fusion, etc.;
(4) Personalized search: Apply large-scale machine learning to solve the recommendation problem in search, and make search more personalized and understand you better;
(5) Hundreds of billions of data: from large-scale offline computing, distributed system performance, scheduling optimization, to building high-availability, high-throughput, and low-latency online services, there are in-depth research and innovation.