Research Scientist Graduate (TikTok Recommendation-Large Recommender Models) - 2026 Start (PhD)

Responsibilities

• Research and develop large-scale recommender systems for personalized, engaging user experiences, focusing on scalability, accuracy, and performance.
• Apply advanced machine learning and deep learning techniques to optimize recommendation algorithms for TikTok’s diverse user base.
• Manage the end-to-end lifecycle of recommender models, from training and fine-tuning to deployment, monitoring, and continuous improvement.
• Analyze complex data to uncover user preferences, behaviors, and trends, driving personalization and enhancing TikTok’s recommendation capabilities.
• Collaborate with cross-functional teams (infrastructure, product, research, etc.) to design and implement innovative solutions that improve the relevance and diversity of TikTok recommendations.

Qualifications

• Minimum Qualifications: Individuals who are completing or have recently completed a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
• Experience in one or more areas of recommender systems, machine learning, computer vision, or natural language processing.
• Proficiency in programming skills, solid foundation in data structures and algorithms.
• Strong familiarity with deep learning architectures such as transformers, CNNs, RNNs, LSTMs, etc.
• Excellent analytical and problem-solving skills, with the ability to collaborate effectively in cross-functional teams.