Senior ML Engineer: Low-Latency pCTR & TPU Architect

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

Benefits offered by this job

Equity

Onsite wellness facilities

Comprehensive benefits

Job summary

Google in Mountain View, CA is hiring a Machine Learning Engineer to design and deploy low-latency pCTR models for Search and Shopping Ads. You will collaborate across Ads ML and research teams to translate user signals into production improvements.

Role focuses on scalable architectures, TPU utilization, and agentic ML workflows to accelerate model discovery while meeting strict compute and ROI constraints.

Qualifications

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

Skills

Software development

Large-scale ML

Deep learning

Neural networks

Recommendation systems

Cross-functional leadership

Education

Bachelor's degree

PhD preferred

Tools

TPU

AdBrain

Admixer

Job description

Google in Mountain View, CA is hiring a Machine Learning Engineer to design and deploy low-latency pCTR models for Search and Shopping Ads. You will collaborate across Ads ML and research teams to translate user signals into production improvements.

Role focuses on scalable architectures, TPU utilization, and agentic ML workflows to accelerate model discovery while meeting strict compute and ROI constraints.