Senior Software Engineer, Generative AI, Search Ads Personalization

Senior Software Engineer, Generative AI, Search Ads Personalization corporate_fare Google place Mountain View, CA, USA bar_chart Mid Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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 state of the art GenAI techniques (LLM, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

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. About the job The US base salary range for this full-time position is $174,000-$252,000 + 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 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 . Responsibilities 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. Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.