Software Engineer, ML, Search Ads Creatives

Software Engineer, ML, Search Ads Creatives Share Software Engineer, ML, Search Ads Creatives _corporate_fare_ Google _place_ Mountain View, CA, USA **Mid** Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Software Engineer, ML, Search Ads Creatives _info_outline_ XIn most instances, this position requires in-person interviews during the hiring process. **Minimum qualifications:** + Bachelor’s degree or equivalent practical experience. + 2 years of experience with software development in Python, or 1 year of experience with an advanced degree. + 2 years of experience ML/AI algorithms, tools, deep learning, or other AI/ML modeling. + 1 year of experience building and deploying recommendation systems models (e.g., retrieval, prediction, ranking, personalization, search quality, embedding) in production. + 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). **Preferred qualifications:** + Master's degree or PhD in Computer Science or a related technical field. + 2 years of experience with data structures and algorithms. + Experience developing accessible technologies. + Experience in GenAI related model fine tuning, large language models building or product enablement exploration. + Deep familiarity with Search/Ads infrastructure, auction mechanics, or generative AI models. **About the job** 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 be part of Search Ads and Ads on Google Experiences, creating useful ads that address user needs, complete tasks, and deliver meaningful return on investment (ROI) for advertisers. You will partner with Product, Sales, Marketing, Buyside Platform, and Policy teams. Ad Creatives sits at the heart of this experience, driving automation and transforming our product for an AI-first world. You will help compose ads meeting user and advertiser needs. GenAI accelerates building and shipping products that automate generating and composing 'high quality' assets and monetizing new AI surfaces. 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: $147000 - $210000 (USD) + 15% bonus target + equity + benefits Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) . **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). + Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. + Build and deploy recommendation systems models, utilize ML infrastructure, and contribute to model optimization and data processing. + Work with and finetune LLMs for targeting, large-scale retrieval, pseudo-rater, and other Ads applications. 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