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X In most instances, this position requires in-person interviews as part of the hiring process.
Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages.
- 1 year of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
- 1 year of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- Experience with mathematics or analytics, with experience analyzing large-scale data.
Preferred qualifications:- Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field.
- 2 years of experience designing, training, and launching machine learning or deep learning models in production.
- Experience in ads ranking, conversion rate prediction, recommendation systems, or auction and bidding optimization.
- Experience with mobile advertising measurement, privacy-preserving attribution signals, or learning from sparse, delayed, or biased feedback.
- Ability to drive cross-functional machine learning and measurement projects end-to-end from problem formulation to production launch.
About the jobJoin the YouTube Ads Machine Learning team to build and scale next-generation conversion prediction models and privacy-safe measurement foundations for YouTube Demand Gen and App Ads on iOS. In this role, you will manage high-impact machine learning and attribution challenges, bridging deep learning modeling, causal/counterfactual evaluation, and privacy-preserving signals to drive revenue and advertiser return on investment (ROI) across YouTube performance ad products.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - 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.
