Software Engineer, YouTube Ads, Modeling Infrastructure

• Bachelor's degree or equivalent practical experience.
• 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or with compute technologies, storage or hardware architecture.
• 2 years of experience in programming in C++ and Python, software engineering, infrastructure design, and machine learning infrastructure.

• Master's degree or PhD in Computer Science or related technical fields.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• 2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
• Experience developing accessible technologies.
• Experience in building large-scale machine learning or AI systems for real world applications.
• Proficiency in code and system health, diagnosis and resolution, and software test engineering.

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.

Our team's mission is to build a centralized, scalable, and real-time platform for brand understanding in YouTube videos, by leveraging multi-modal Gemini models at YouTube scale. Our high-quality brand annotations will power a wide range of applications, from ad targeting, creator discovery for influencer marketing (Brand Connect) to strategic planning and reporting tools. Our understanding of brands in videos will enable new product directions and innovation in ad formats making brand advertising more effective for advertisers, more engaging for users and providing business generation opportunities for creators. The issue is to leverage AI techniques at a very large-scale with limited resources requiring innovation in modeling infrastructure.

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.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

• Write product or system development code. Build modeling infrastructure to engineer high performance solutions at YouTube scale, specifically large-scale Machine Learning solutions for solving video understanding problems that impact many new and critical applications in YT Ads. Design, build, and maintain the infrastructure for our real-time brand annotation platform.
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• 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.
• Lead collaborations with client teams, VIA infrastructure, ML research teams, and more.