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

TikTok 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 Us

At 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.