Machine Learning Engineer - TikTok Lead Ads

TikTok 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 UsCreation 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. The Lead Ads team empowers TikTok's global monetization (billion-dollar business) via efficiently delivering lead ads on TikTok. Our mission is to push the boundaries of large-scale ads delivery systems and lead the innovations of TikTok's personalized online advertising. Hence, you'll have a chance to get deeply involved in our large-scale distributed systems and state-of-the-art machine learning algorithms. As a Machine Learning Engineer on the Lead Ads team, you will make efforts to develop novel machine learning solutions for ranking, build scalable foundations and launch various products that maximize the efficiency of lead ads delivery. Key Responsibilities : - Work on the development of a large-scale online ads delivery system and improve its accuracy.- Explore multi-stage ranking models, conduct data analysis, develop feature engineering.- Participate in the innovations of online ads systems using machine learning models, ranking algorithms, etc.- Partner with product managers, data scientists and product strategy & operation team to launch new Lead Ads products and features.

Minimum Qualifications : - BS / MS degree in Computer Science, Computer Engineering, or other relevant majors.- Hands-on experience with applying machine learning methods for ranking.- Strong software development experience and strong coding skills, especially in Python / C++. Experience with Tensorflow / PyTorch / MXNet is a plus.- Experience with recommender system projects.- Familiarity with online experimentation methods and analytics. Essential knowledge and skills in statistics.- Curiosity toward new technologies and entrepreneurship.