Principal Engineer, Shopping Product Graph & Data Infra

Google Inc.; Pittsburgh (Allegheny County); On-site; USD 262,000 - 364,000; Full time

Job summary

Google Pittsburgh, PA, USA is seeking a Lead Engineer to own the Shopping Product Graph within Data Infrastructure. You will guide ML-driven data infrastructure, scale, and feature sets for computing on billions of products and relationships. This role emphasizes leadership across engineering velocity and experimentation.

We value deep ML architecture expertise, system design, and the ability to influence stakeholders in a fast-paced environment that spans Search, Gemini, YouTube, and Ads.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in machine learning architecture.
• Experience with graph storage and knowledge base systems.
• Experience with data pipeline infrastructure and quality.
• Experience leading engineering velocity and experimentation.

Responsibilities

• Set the technical outlook and design the data infrastructure to support the necessary scale, resilience, and rich feature set that clients depend on.
• Write robust code to solve ambiguous, large-scale problems.
• Enable fast iterations on product graph quality through data-driven decision-making supported by experiments and evaluations.
• Collaborate closely with cross-product area partners to translate techniques into tangible, real-world product impact.
• Work with other engineering leads, Product Managers, and executives to identify areas for further improvement in the broader shopping graph.

Skills

ML architecture

Leadership

Experimentation

Stakeholder influence

Education

Bachelor's degree or equivalent practical experience

Master’s degree or PhD in Engineering/CS

Tools

Graph storage systems

Knowledge base systems

Data pipeline infrastructure

Job description

Google Pittsburgh, PA, USA is seeking a Lead Engineer to own the Shopping Product Graph within Data Infrastructure. You will guide ML-driven data infrastructure, scale, and feature sets for computing on billions of products and relationships. This role emphasizes leadership across engineering velocity and experimentation.

We value deep ML architecture expertise, system design, and the ability to influence stakeholders in a fast-paced environment that spans Search, Gemini, YouTube, and Ads.