Design, train, and launch large-scale deep learning models (such as pCVR, pInstall, pEvent, pValue, and presence models) to improve conversion prediction accuracy and advertiser return on investment (ROI) on iOS. Develop and integrate privacy-preserving measurement and attribution signals. Diagnose and resolve complex label-bias, calibration, and counterfactual evaluation challenges across online auction and bidding systems.
Build and maintain scalable ML training, feature engineering, and model-serving pipelines. Partner closely with Product Management, Research, and Ads Serving/Bidding infrastructure teams to drive projects end-to-end, from large-scale data analysis and offline prototyping to online A/B experimentation and production launches.
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