Staff AI/ML Engineer for YouTube Ads

Google LLC; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google LLC seeks a Staff Software Engineer, AI/ML for YouTube Ads to advance AI-driven ad creation, personalization, and optimization at scale. You will lead the design and deployment of ML models that power ad experiences across billions of YouTube users, collaborating across research, ads, and platform teams.

You will work on deep learning, reinforcement learning, and generative AI, building large-scale serving platforms, experimentation frameworks, and measurement to ensure creative freshness

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.

Responsibilities

• Lead end-to-end development of ML models (deep learning, RL, generative AI) from concept to production.
• Build and scale ML pipelines for training, inference, and integration with high-throughput Ad serving systems.
• Explore and integrate generative models for text, image, and video adaptations within Ads.
• Apply deep learning and reinforcement learning to optimize creative composition while developing metrics and exploration algorithms.
• Contribute to architecture of centralized services for asset attributes and model-driven insights across apps.

Skills

Machine learning

Deep learning

Reinforcement learning

Generative AI

Model deployment

A/B testing

Advertising tech

Education

Bachelor's degree

Master's degree

PhD

Tools

TensorFlow

JAX

TensorFlow Extended

AdBrain

Job description

Google LLC seeks a Staff Software Engineer, AI/ML for YouTube Ads to advance AI-driven ad creation, personalization, and optimization at scale. You will lead the design and deployment of ML models that power ad experiences across billions of YouTube users, collaborating across research, ads, and platform teams.

You will work on deep learning, reinforcement learning, and generative AI, building large-scale serving platforms, experimentation frameworks, and measurement to ensure creative freshness