Staff ML Software Engineer, YouTube Ads Creative Optimization

Minimum Qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred Qualifications:

• Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
• Experience with Generative AI, including large language models (LLMs) and diffusion models.
• Experience leading complex, cross-functional projects from conception to launch.
• Experience working as a Tech Lead or in a similar leadership role.
• Understanding of advertising systems and metrics.

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.

The YouTube Ads Creative Optimization team is at the forefront of revolutionizing YouTube Ads through the power of Machine Learning and Generative AI. Our mission is to empower advertisers with creative optimization solutions that automatically generate and optimize high-performing ad creatives.

We are a cross-functional team of engineers, product managers, and designers who work on solving complex issues in a changing, innovative environment. In this role, you will be working on projects with a direct and measurable impact on Google's business and its advertisers.

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 $197,000-$291,000 + 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

• Design, develop, and deploy machine learning models and infrastructure for creative generation and optimization.
• Lead technical discussions and drive the team's engineering roadmap for ML-powered features.
• Work with Generative AI models to create novel ad formats and experiences.
• Collaborate with product managers and other stakeholders to define project requirements and deliverables.
• Mentor and guide junior engineers on the team.