Senior ML Engineer — Search & Shopping Ads

Google; Mountain View (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google is seeking a software engineer to lead the architecture and delivery of Search and Shopping Ads predicted click‑through‑rate (pCTR) models in close partnership with DeepMind, Research, and Ads ML teams. You will design low-latency architectures that maximize TPU capabilities while meeting strict latency and ROI goals.

Responsibilities include developing modeling solutions to capture deep user history, engineering loss functions for auction dynamics, and deploying AI workflows to

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of software development experience, including 5 years in large-scale machine learning, deep learning, neural networks, or recommendation systems.
• Experience designing and implementing large-scale production deep learning architectures under latency 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 pCTR models with DeepMind, Research, and Ads ML teams.
• Design, prototype, and scale high-capacity pCTR architectures maximizing TPU capabilities within low-latency serving and ROI budgets.
• Develop modeling solutions to capture deep user history and attention signals, integrating ads into AI experiences like AI Overviews and AI Mode.
• Engineer loss functions and calibration methods translating business objectives into improvements.
• Build agentic ML workflows to automate model architecture and feature space discovery.

Skills

Large-scale ML

Production DL architectures

Cross-functional leadership

Mentoring engineers

Education

Bachelor’s degree or equivalent

PhD preferred in CS/ML

Tools

TPU

Job description

Google is seeking a software engineer to lead the architecture and delivery of Search and Shopping Ads predicted click‑through‑rate (pCTR) models in close partnership with DeepMind, Research, and Ads ML teams. You will design low-latency architectures that maximize TPU capabilities while meeting strict latency and ROI goals.

Responsibilities include developing modeling solutions to capture deep user history, engineering loss functions for auction dynamics, and deploying AI workflows to