About the team On the TikTok Search Team, you will have the opportunity to develop and apply cutting edge machine learning technologies in real-time large-scale systems, which serve billions of search requests every day. Via advanced NLP and multi-modal models, our projects impact and improve the search experience for hundreds of millions of users globally. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving. About the Role TikTok is seeking a visionary and technically adept leader to head our Personalized Search team. This role is pivotal in advancing TikTok's search capabilities by integrating cutting-edge recommendation algorithms and Large Language Model (LLM) technologies to deliver highly personalized and engaging user experiences. Responsibilities - Technical Leadership: Lead the design, development, and deployment of large-scale personalized search and recommendation systems, ensuring scalability, efficiency, and robustness. - Innovation with Generative Recommendation Systems: Drive the integration of generative recommendation approaches, leveraging LLMs to directly generate personalized content recommendations, moving beyond traditional ranking-based methods. This includes exploring frameworks like GenRec, which utilize LLMs to interpret user contexts and generate relevant recommendations. - LLM Integration: Implement and fine-tune LLMs within the recommendation pipeline to enhance content understanding, user intent recognition, and personalization. Explore hybrid models that combine LLMs with traditional recommendation systems to mitigate feedback loops and uncover novel user interests. - Research and Development: Stay abreast of the latest advancements in machine learning, NLP, and recommendation systems, applying relevant findings to improve TikTok's search experience. - Cross-functional Collaboration: Work closely with product managers, data scientists, and infrastructure engineers to align search personalization strategies with overall product goals. - Team Development: Mentor and grow a team of engineers and researchers, fostering a culture of innovation, collaboration, and continuous learning.
Minimum qualifications - Educational Background: Bachelor's or advanced degree in Computer Science, Machine Learning, or a related field. - Experience: 5+ years in developing large-scale search or recommendation systems, with at least 2 years in a leadership role. - Technical Expertise: Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, C++), and deep understanding of data structures and algorithms. - Generative Recommendation Systems: Hands-on experience with deploying and fine-tuning LLMs for real-world applications, including techniques like prompt engineering and retrieval-augmented generation. Familiarity with generative recommendation frameworks and their application in large-scale systems is highly desirable. - Publications: Contributions to top-tier conferences such as NeurIPS, ICML, ACL, or RecSys are a plus. Preferred Qualifications - Industry Recognition: Recognized thought leader in the fields of search personalization and recommendation systems. - Global Experience: Experience working with international teams and understanding of diverse user behaviors across different regions. - Open Source Contributions: Active participation in open-source projects related to search, recommendation, or NLP.
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