Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. In this role, you will have the opportunity to learn and improve key components of the Google Ads serving system. You will get deep insights into how different interconnected components interact and sometimes compete. You will drive ad quality and feature initiatives to deliver excellent experiences for users and advertisers, creating long-term ads value. Your work involves identifying system opportunities or gaps, designing data-driven improvements, and executing launch plans through rigorous metric analysis. If you are passionate about machine learning, GenAI, system design, distributed systems, ads quality/feature, or a combination thereof, you will have the opportunity to drive large-scale projects and optimize the Google Ads ecosystem. 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 • Write product or system development code. • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). • Evaluate ads performance and find quality/revenue opportunities through open-ended data-mining utilizing offline approaches (e.g., log analysis, machine learning, simulations, headroom analysis), and experiment approaches (e.g., holdback, counterfactual, tuning grid). Develop metrics, pipelines, and dashboards to guide projects and measure launch impacts. • 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. • Enhance user, advertiser, and Google value, focusing on offline/omni shopping ads by refining ML models, auction, ads triggering (query understanding), bidding, scoring, content generation and selection, format/UI, etc. 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, optimization, 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. Preferred qualifications: • Master's degree or PhD in Computer Science or related technical fields. • 2 years of experience with data structures and algorithms. • Experience developing accessible technologies. • Experience in analytics.