Machine Learning Engineer , TikTok Search Ranking
Posted 15 days ago
Job Description
The Search Ranking Team is the core algorithm team of TikTok Search business. We are responsible for optimizing user experience in the search and recommendation scenario. We have opened full-link algorithm positions such as indexing, recall, rough sorting, fine sorting, rerank, and mix-rank. Here you’ll have the opportunity to build a full-stack search engine system based on advanced AI methods to provide a world leading search engine. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.
Responsibilities
1. Using cutting-edge information retrieval and machine learning technologies, develop industry-leading search and recommendation algorithms that directly enhance the real experience of billions of global users. Here, you will have the opportunity to work on numerous advanced challenges such as optimizing trillion-scale index libraries, models with trillions of parameters, ultra-long user sequence modeling, and large-scale sparse models.
2. Deeply explore how large-scale models will disrupt the next generation of search, recommendation, and ranking models, fully leveraging the world knowledge embedded in these models to bring revolutionary transformations to search and recommendation services. Here, you will have the opportunity to work with the industry’s most cutting-edge technologies such as short-video multimodal understanding, generative models, scaling laws, sparse MoE, and reinforcement learning, harnessing massive computational power to become a highly sought-after talent!
3. Combine your understanding of product objectives and take full advantage of modern machine learning, AI, NLP/CV techniques to improve the search ranking algorithms, including query understanding, video understanding and various levels of result ranking.
Minimum Qualifications
1. Bachelor degree or above in the field of computer science or a related technical discipline
2. Proficient coding skills and strong algorithm & data structure using C++/Python/Java
3. Have a solid knowledge of machine learning and practical experience in applying it
Preferred Qualifications
1. Effective communication and teamwork skills.
2. Modeling experience in one or more of the following areas: Ads, Search engine, Recommender System, NLP/CV
Responsibilities
1. Using cutting-edge information retrieval and machine learning technologies, develop industry-leading search and recommendation algorithms that directly enhance the real experience of billions of global users. Here, you will have the opportunity to work on numerous advanced challenges such as optimizing trillion-scale index libraries, models with trillions of parameters, ultra-long user sequence modeling, and large-scale sparse models.
2. Deeply explore how large-scale models will disrupt the next generation of search, recommendation, and ranking models, fully leveraging the world knowledge embedded in these models to bring revolutionary transformations to search and recommendation services. Here, you will have the opportunity to work with the industry’s most cutting-edge technologies such as short-video multimodal understanding, generative models, scaling laws, sparse MoE, and reinforcement learning, harnessing massive computational power to become a highly sought-after talent!
3. Combine your understanding of product objectives and take full advantage of modern machine learning, AI, NLP/CV techniques to improve the search ranking algorithms, including query understanding, video understanding and various levels of result ranking.
Minimum Qualifications
1. Bachelor degree or above in the field of computer science or a related technical discipline
2. Proficient coding skills and strong algorithm & data structure using C++/Python/Java
3. Have a solid knowledge of machine learning and practical experience in applying it
Preferred Qualifications
1. Effective communication and teamwork skills.
2. Modeling experience in one or more of the following areas: Ads, Search engine, Recommender System, NLP/CV
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