Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 2 years of experience programming in Python or C .
- 1 year of experience with end to end machine learning (e.g., model deployment, model evaluation, data processing, debugging).
Preferred qualifications:- Master's degree or PhD in Computer Science, Stastics, Mathematics, or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience in investigative frameworks, statistics, or mathematics.
- Experience developing accessible technologies.
About the jobAs a part of the Gmail Ads Quality organization, your main focus area is to improve Gmail Ads personalization and advertiser value optimization by applying machine learning in auction models (predicted click-through-rate, predicted conversions, bidding, etc.), supporting new advertiser features and optimizing end-to-end campaign performance.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We're made up of multiple teams, building Google's Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $211000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities- Write product or system development code.
- Build and implement machine learning models and optimization algorithms.
- Design, run, analyze and launch experiments.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Implement solutions in one or more specialized ML areas and contribute to model optimization and data processing.
