Responsibilities span the full modeling lifecycle, including training data and labeling strategy, feature and signal design, model development, and rigorous offline and online evaluation. Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance. Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications. 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) Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. Proven experience in programming and data analysis skills. Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM. 5+ years of experience in developing and deploying large-scale machine learning models.
