Senior Software Engineer, Generative AI, Agentic Creatives Optimization, YouTube Ads

corporate_fareYouTubeplaceMountain View, CA, USA

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  
• 1 year of experience with GenAI techniques (e.g., LLMs, 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.
  
• 2 years of experience with Machine Learning and Deep Learning frameworks (e.g., TensorFlow, PyTorch).
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.

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.

YouTube Ads is a billion dollar business and the fastest growing segment of Google's Ads. Our mission is to power the YouTube ecosystem by keeping it free and engaging for users, responsibility rewarding creators and connecting businesses to their unique audiences.

The YouTube Ads Creative Optimization (YACO) team drives the mission to effectively connect businesses and users with the best creative technology. We specialize in Creative Automation applications that drive advertiser value with minimal advertiser effort through leveraging the AI technologies. This team uniquely grows at the intersection of Ads, YouTube and Research.

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 $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 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.

Responsibilities

• Write and test product or system development code.
• 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.
• Develop machine learning models and infrastructure for creative generation and optimization, working with Technical Lead to finalize the design. Participate in technical discussions and contribute to the team's engineering goals.
• Work with GenAI and ML models to create novel ad formats and experiences. Collaborate with product managers and other stakeholders to understand project requirements and deliverables. Debug issues and contribute to the overall stability and improvement of the team's infrastructures.