Programmatic Bidding Science Expert

R&D Family - Terminal Cloud Technology Laboratory-Boyle Research Centre

• Responsible for the advancement and effectiveness of large-scale advertising recommendation model technologies, including but not limited to the application of LLM in advertising recommendations, massive parameter models, real-time incremental updates, sparse scenario predictions, and other technologies.
• Responsible for the application outcomes of large-scale advertising recommendation model technologies, including the performance of recommendation models in terms of pCTR, pCVR, acceptance rate, etc.

Position Requirements

• Master/PhD in Computer Science, Statistics, Machine Learning, Deep Learning, or related fields. Prior experience in advertising bidding, reinforcement learning, auction mechanism design, game theory is preferred.
• Familiar with the latest technologies in bidding mechanisms and algorithms, with a preference for those who have published relevant papers/posters in top journals/conferences/workshops. Strong technical foresight and staying up-to-date, capable of quickly following and digesting new industry-leading technologies to drive the company's technological advancements.
• Proven experience in research and application of bidding strategy frameworks and billing mechanisms. Familiar with bidding paradigms and successful application experiences in smart bidding, budget pacing, cold start strategies, campaign stability, anti-fraud, attribution, etc.

Location

Ireland/Dublin

Department

Terminal Cloud Technology Laboratory-Boyle Research Centre