Staff GenAI Engineer — Large-Scale Semantic Retrieval

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

Job summary

Google's YouTube team in San Bruno, CA seeks a Staff Software Engineer for GenAI Applications, focusing on scalable retrieval and data analytics. You will own end-to-end architecture, design context retrieval, and ship production-grade features that scale to billions of users.

You will lead technical strategy, mentor senior engineers, and collaborate with Google DeepMind and YouTube infrastructure to apply research to real-world systems.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning, or natural language processing.

Responsibilities

• Design and implement dynamic context construction strategies for RAG (Retrieval Augmented Generation) systems.
• Solve challenges related to limited context versus massive schema documentation, optimizing for precision, recall, and cost.
• Lead the evaluation and fine-tuning of embedding strategy (dense, sparse, and hybrid) to capture domain-specific YouTube terminology.
• Build data pipelines that keep our semantic index fresh in real-time as YouTube's data schemas evolve.
• Mentor Senior Engineers, drive technical roadmap planning, and collaborate with partners in Google DeepMind and YouTube infrastructure to adopt research.

Skills

Software development

Machine learning

Context retrieval

Data pipelines

SQL

LLM basics

Education

Bachelor's degree

Tools

TensorFlow

Python

Job description

Google's YouTube team in San Bruno, CA seeks a Staff Software Engineer for GenAI Applications, focusing on scalable retrieval and data analytics. You will own end-to-end architecture, design context retrieval, and ship production-grade features that scale to billions of users.

You will lead technical strategy, mentor senior engineers, and collaborate with Google DeepMind and YouTube infrastructure to apply research to real-world systems.