About the job

The YouTube Ads' 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 AI technologies. This team uniquely grows at the intersection of Ads, YouTube, and Research.

As Director of Engineering, you will be responsible for the Creatives for YouTube Ads, including asset acquisition, asset quality evaluation, and asset generation and enhancement utilizing the evolving AI/ML technology.
The US base salary range for this full-time position is $307,000-$427,000 + 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

• Partner closely with Product Management leadership to define the outlook and opportunities for media creation and enhancements, especially utilizing AI with a focus on Video.

• Identify gaps with the current offerings and develop solutions to address them, contributing to YouTube engineering leadership on Ads-wide initiatives.

• Take responsibility for the overall planning, execution, and success of complex technical projects.

Minimum qualifications

• Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.

• 15 years of experience in engineering, and experience with technical innovation.

• Experience leading full stack engineering, distributed systems teams, or quality teams.

• Experience with AI or computer vision technologies.

Preferred qualifications

• Experience leading teams building and shipping complete end-to-end consumer products with an element of AI/ML as the underlying technology.