Staff AI/ML Software Engineer, YouTube Ads Creative Foundations

Minimum qualifications

• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing and launching software products.
• 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
• 3 years of experience with software design and architecture.
• Experience designing or deploying machine learning (ML) infrastructure or platforms.

Preferred qualifications

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
• Proficiency in deep learning frameworks (e.g., TensorFlow, PyTorch) and cloud/distributed data technologies.

About the job

Develop next-generation technologies that operate at massive scale. Work on a project critical to business needs, with opportunities to switch teams and projects as priorities evolve. Bring ideas across areas including distributed computing, large-scale system design, networking, data storage, artificial intelligence, and more.

Manage project priorities, deadlines, and deliverables. Design, develop, test, deploy, maintain, and enhance software solutions.

The YouTube Ads Creative Optimization (YACO) team develops Creative Automation applications that drive advertiser value with minimal advertiser effort by leveraging AI technologies. The team operates at the intersection of Ads, YouTube, and Research.

Responsibilities

• Serve as the technical leader responsible for architecting, scaling, and steering next-generation infrastructure that powers AI/ML applications.
• Operate at the intersection of Ads, YouTube, and GenAI research to build high-throughput systems enabling seamless creative generation and optimization.
• Define the technical roadmap and architect scalable foundational infrastructure, including creative data engines, generation and rendering pipelines, and agentic orchestration frameworks.
• Design and optimize distributed systems for complex GenAI and heavy media-processing workloads.
• Build and mature experiment and learning infrastructure to accelerate model training, evaluation, and rapid deployment.
• Partner with Product Management, Research, and executive leadership to align infrastructure capabilities with long-term business goals.
• Guide, mentor, and elevate executive and junior engineers, fostering technical excellence and execution.