Senior ML Engineer, Search & Shopping Ads

Google; United States; On-site; USD 262,000 - 364,000; Full time

Job summary

Google is seeking a Machine Learning Engineer for Search and Shopping Ads to own the design and deployment of advanced pCTR models. You will work with DeepMind, Research, and Ads ML to craft low-latency, high-throughput architectures and loss functions aligned with business metrics.

You will influence model discovery through agentic workflows and collaborate with multiple teams to advance AI-driven advertising solutions at scale.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience with software development, including 5 years with large-scale machine learning, deep learning, neural networks, or recommendation systems.
• Experience designing and implementing large-scale production deep learning or neural network architectures under latency and computational constraints.
• Experience leading cross-functional technical projects and mentoring other engineers.

Responsibilities

• Lead the technical architecture, delivery, and cross-team strategy for Search and Shopping Ads predicted click-through rate (pCTR) models in close partnership with DeepMind, Research, and Ads ML teams.
• Design, prototype, and scale high-capacity pCTR architectures that maximize TPU capabilities while meeting low-latency constraints.
• Develop modeling solutions to capture deep user history and attention signals, integrating ads into AI Search experiences.
• Engineer loss functions and calibration methods, translating business objectives into top-line improvements.
• Build agentic ML workflows to automate model architecture and feature discovery.

Skills

Large-scale ML

Production DL architectures

Cross-functional leadership

Mentoring engineers

Latency optimization

Education

Bachelor's degree or equivalent

PhD preferred

Job description

Google is seeking a Machine Learning Engineer for Search and Shopping Ads to own the design and deployment of advanced pCTR models. You will work with DeepMind, Research, and Ads ML to craft low-latency, high-throughput architectures and loss functions aligned with business metrics.

You will influence model discovery through agentic workflows and collaborate with multiple teams to advance AI-driven advertising solutions at scale.