Senior Software Engineer, Semantic Understanding, Search Ads Personalization

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. Semantic understanding is the ability to comprehend the actual meaning, intent, and context of words, symbols, or language rather than just recognizing individual keywords or surface-level grammar. Our personalization models are only as good as our understanding of the content users interacted with. In this role, you will focus on end-to-end enriching personalization stack with real-time understanding of user interactions with content pieces (for eg. what was the content of the page or video? How can we instantaneously bring in rich information as features for our personalization models to adapt to the user's emergent interests?). Your responsibilities will include collaborating across modeling and infrastructure teams across Ads, to build real-time infrastructure and representations of user viewed content, as the primary growth driver of our impact and accuracy.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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . Write and test product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. 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. Build real-time infrastructure and representations of user viewed content. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience programming in Python or C++. 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging). 2 years of experience with Large Language Model (LLMs), Multi-Modal, or Large Vision Modeling. Preferred qualifications: Master's degree or PhD in Computer Science or related technical field. 5 years of experience with data structures and algorithms. 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. 1 year of experience in a technical leadership role. Experience developing and optimizing machine learning algorithms for personalization, ranking, and content recommendation. Bachelor’s degree or equivalent practical experience. 5 years of experience programming in Python or C++. 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging). 2 years of experience with Large Language Model (LLMs), Multi-Modal, or Large Vision Modeling.