Data Quality Architect for AI & ML Pipelines

Google LLC; San Jose (CA); On-site; USD 307,000 - 427,000; Full time

Job summary

Google is seeking a Principal Engineer, Data Quality, AI Foundry in the United States to lead the technical direction for data quality across high-scale ML training data and Search contexts. You will collaborate with DeepMind, Search teams, and infrastructure owners to evolve systems for reliable, scalable data pipelines.

The role drives the data quality strategy, defines metrics, and guides critical components to ensure data is trustworthy and ready for production AI models.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, a related technical field, or equivalent practical experience.
• 15 years of experience in software engineering, building and working with systems in the technology organization.
• 7 years of experience in a technical leadership role with/without direct reports.
• 5 years of experience developing and deploying machine learning models on data sets.
• 3 years of infrastructure or data systems experience building or managing infrastructure products, such as distributed storage systems, data warehousing, or data processing pipelines.

Responsibilities

• Lead the strategy, technical vision, and roadmaps for the data quality team to deliver high-quality datasets for DeepMind and Search.
• Drive the architecture toward establishing the data flywheel for ML training data and Search Context that can self correct and self heal as the data travels through multiple dynamic and large-scale systems (such as sourcing, acquisition and indexing) to the data store.
• Collaborate closely with DeepMind and Search researchers, data analysts, and engineers to identify key Value of Data (VoD) signals.
• Partner with infrastructure owners in AI Foundry to evolve systems—including crawl, processing, and signal enrichment—to deliver high-quality datasets that power Search features and AI models.
• Provide technical guidance to critical components of the context quality area, such as large-scale signal developments, design and development of quality metrics.

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, a related technical field, or equivalent practical experience

Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field

Job description

Google is seeking a Principal Engineer, Data Quality, AI Foundry in the United States to lead the technical direction for data quality across high-scale ML training data and Search contexts. You will collaborate with DeepMind, Search teams, and infrastructure owners to evolve systems for reliable, scalable data pipelines.

The role drives the data quality strategy, defines metrics, and guides critical components to ensure data is trustworthy and ready for production AI models.