Write product or system development code and manage serving training resources for the entire YouTube Ads ML team to redeploy saved resources on new initiatives.

Build and deploy recommendation systems models, utilize ML infrastructure, and contribute to model optimization and data processing.

Develop and maintain automation/co-pilot frameworks for feature selection, health monitoring, resource savings, and abnormal metrics investigation alongside back-ends supporting feature engineering.

Maintain the predictions back-end by preparing and transforming features at serving time, while developing monitoring alerting for the entire model fleet.

Guide fleet-wide training infrastructure modernization by working closely with ML modeling teams on signals development, model training, and serving.

Bachelor’s degree or equivalent practical experience.

2 years of experience with software development in one or more programming languages (e.g., C++), or 1 year of experience with an advanced degree.

1 year of experience building and deploying recommendation systems models (e.g., retrieval, prediction, ranking, personalization, search quality, or embedding) in production.

1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).