Staff AI/ML Engineer — Generative Ad Tech at Scale

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

Job summary

Google is seeking a software engineer to advance AI-driven ad creativity at scale. You will lead end-to-end machine learning model development, manage data pipelines for training and inference, and integrate generative AI into ad experiences serving billions of YouTube users.

Role involves deep learning, reinforcement learning, and large-scale serving platforms, with collaboration across Google Research and DeepMind to push state-of-the-art in advertising technology.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8+ years of experience in software development.
• 5+ years testing and launching software products, and 3+ years in software design and architecture.
• Preferred: Master's or PhD in CS/ML or related field.
• 8 years of experience in data structures and algorithms.
• 5 years building and productionizing ML models including deep learning or reinforcement learning.

Responsibilities

• Lead end-to-end development of novel ML models 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 and metrics.
• Contribute to architecture of centralized services for asset attributes and model-driven insights.

Skills

8+ years software development

A/B testing

large-scale systems

ML model deployment

Deep learning

Education

Bachelor's degree or equivalent

Master's or PhD in CS/ML or related field

Tools

TensorFlow

JAX

TFX/AdBrain

Job description

Google is seeking a software engineer to advance AI-driven ad creativity at scale. You will lead end-to-end machine learning model development, manage data pipelines for training and inference, and integrate generative AI into ad experiences serving billions of YouTube users.

Role involves deep learning, reinforcement learning, and large-scale serving platforms, with collaboration across Google Research and DeepMind to push state-of-the-art in advertising technology.