Tiktok - San Jose, CA
posted 3 months ago
TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. The Core Feed Recommendation team is at the heart of TikTok, responsible for designing, implementing, and improving the core recommendation algorithms that power the "for you" and "following" feeds of the TikTok app. This recommendation system connects hundreds of millions of users with relevant content from billions of videos in real-time, fostering high-quality content creation for millions of creators on the platform. The User Growth team, a vital part of the Core Feed Recommendation team, focuses on implementing and refining strategies for new user acquisition and retention. We are dedicated to achieving TikTok's overarching goals by developing high-performance models and sound strategies. Our approach is characterized by rigorous applied research, innovative system design, and a commitment to pragmatism. We are seeking strong research scientists and engineers at all levels who are eager to enhance their business understanding, build scalable and reliable software, and collaborate across disciplines with global teams in pursuit of excellence. In this role, you will implement machine learning, recommendation, and causal inference algorithms at scale to optimize new user acquisition efficiency and user retention throughout the user lifecycle. You will work cross-functionally with product managers, data scientists, and product engineers to derive insights, formulate problems, design and refine machine learning algorithms, and drive the exciting growth of TikTok's global user base. Additionally, you will analyze specific issues affecting user growth across various regions and markets, utilizing algorithmic levers for targeted optimization, and run regular A/B tests to iterate algorithms based on performance analysis.