Machine Learning Engineer, TikTok Ads Core - Native Ads & Business Accounts

DescriptionTikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo. Why Join UsAt TikTok, our people are humble, intelligent, compassionate and creative. We create to inspire - for you, for us, and for more than 1 billion users on our platform. We lead with curiosity and aim for the highest, never shying away from taking calculated risks and embracing ambiguity as it comes. Here, the opportunities are limitless for those who dare to pursue bold ideas that exist just beyond the boundary of possibility. Join us and make impact happen with a career at TikTok.We are the Ads Core Team from TikTok Global Monetization Technology. Within the global monetization and advertising landscape, we are responsible for generating revenues through advanced machine learning technology and delivering optimal user experience solutions. Our team's mission is to create automatic delivery products for the next generation, to develop advertising as a business instead of just a monetization tool, and to consolidating the delivery funnel framework allowing multiple teams to iterate parallel. We’re looking for innovative Machine Learning Engineers to develop state-of-art ad technologies, including ranking, retrieval, targeting, bidding, auction, etc. You will be part of a team that's optimizing ads format and ranking strategies, and you will be responsible for bringing a better return on investment for advertisers. What You'll Do• Improve the effectiveness of spark ads delivery in all ads ranking systems, improve user experience and ROI.• Develop open-loop bidding products by joint optimization of recommendation traffic and ads traffic.• Iterate bidding strategy to reach the ROI and CPA goal.• Improve anchor model efficiency, including privacy preserving environments. • Improve user experience, maximize the delivery effect with minimal experience loss.QualificationsMinimum Qualifications:• BS/MS degree in Computer Science, Computer Engineering, or a related technical discipline with model optimization experience.• Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.• Good analytical thinking capability. Have essential knowledge and skills in statistics.• Good theoretical grounding in deep learning concepts and techniques.• Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet), familiar with its architecture and implementation mechanism.Preferred Qualifications:• Good understanding in one of the following domains: ads bidding & auction, ads quality control, and online advertising systems (familiar with one or more of these terms: CPC/CPM, CTR/CVR, Ranking /Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB).• Experience in resource management and task scheduling with large scale distributed software (such as Spark and TensorFlow).TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or reasonable accommodation, please reach out to us at https://shorturl.at/cdpT2 . By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy. RegularExperienced