Job Description

- Design, develop, and train Large Language/Retrieval models for advertising scenarios. - Innovate on model architectures and training strategies to enhance ad retrieval, generation, and relevance at scale. - Build solutions that proactively address ad safety, including detection of deceptive or harmful content. - Collaborate cross-functionally with product and engineering teams to integrate models into production systems and validate their impact. - Lead technical exploration and research efforts, staying at the forefront of advancements in AI and advertising technology. - Mentor junior scientists and contribute to a culture of technical excellence and innovation. Required Qualifications: - Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) - OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) - OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) - OR equivalent experience. - Deep understanding of transformer architectures, large-scale distributed training, and model optimization. - Solid programming skills in Python, C++, and familiarity with frameworks like PyTorch or TensorFlow. Preferred Qualifications: - Experience with ads systems, search ranking, recommendation engines, or ad safety models is highly desirable. - Experience in reinforcement learning, multi-agent systems, or decision-making frameworks.

Skills Required