Staff GenAI Applications Engineer - YouTube Data Analytics

Google Inc.; San Bruno (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google is seeking Staff Software Engineer for GenAI Applications at YouTube. You will architect the semantic layer powering GDA products, define model understanding of YouTube’s data landscape, and own end-to-end context retrieval.

You’ll design, develop, test, deploy, and maintain software solutions while leading technical strategy for large-scale projects and mentoring engineers. Role emphasizes building scalable data-driven systems, collaboration with DeepMind and YouTube teams, and

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of software development experience.
• 5 years testing, launching software products, and 3 years with design/architecture.
• 5 years of experience with ML algorithms and tools (e.g. TensorFlow), AI, deep learning, or NLP.

Responsibilities

• Architect semantic layer powering GDA products like YouTube SQL Assistant.
• Define how models understand YouTube’s data landscape and end-to-end context retrieval.
• Design, develop, test, deploy, maintain, and enhance software solutions.
• Lead context retrieval strategies for RAG systems and embedding strategy evaluation.
• Mentor engineers, drive technical roadmap, and collaborate across teams.

Skills

Software development

Software testing & launch

Software design & architecture

Machine learning

TensorFlow

Natural language processing

SQL

Information retrieval

Vector space models

Data analysis

Education

Bachelor's degree or equivalent

Tools

TensorFlow

Job description

Google is seeking Staff Software Engineer for GenAI Applications at YouTube. You will architect the semantic layer powering GDA products, define model understanding of YouTube’s data landscape, and own end-to-end context retrieval.

You’ll design, develop, test, deploy, and maintain software solutions while leading technical strategy for large-scale projects and mentoring engineers. Role emphasizes building scalable data-driven systems, collaboration with DeepMind and YouTube teams, and