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Design and implement context construction strategies for RAG systems serving YouTube's massive schema, optimizing embedding techniques (dense, sparse, hybrid) and building real-time data pipelines as schemas evolve. Mentor senior engineers and drive technical strategy across large-scale projects. Requires 8 years software development experience, 5 years launching products, 3 years software architecture, and 5 years with ML tools like TensorFlow, AI, deep learning, or NLP.

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Job Description

  • 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. You will decide how we represent data tables, column definitions, and debug logs in vector space.
  • 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.

Minimum 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.

Preferred qualifications:

  • 8 years of experience with data structures and algorithms.
  • Experience leading technical strategy for large-scale projects and mentoring executive engineers.
  • Experience designing and implementing complex context retrieval systems (context scaffolding) for large language models in production.
  • Proficiency in SQL.
  • Understanding of vector space models, semantic search, and experience evaluating embedding techniques (e.g., dense versus sparse retrieval, re-ranking strategies).
  • Ability to independently query massive datasets to diagnose model behavior, identify edge cases, and drive data-informed architectural decisions.
  • 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.
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  • Role Staff Software Engineering, GenAI Applications, YouTube
  • Experience 8-9 years
  • Education Bachelor Degree, or equivalent experience
  • Work type On-site
  • Location United States
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Google
AI Research Lab · 500+ Members · Mountain View, CA, United States

Google builds internet, software, cloud, and AI products used by consumers, developers, and organizations. Its portfolio includes Search, YouTube, Android, Chrome, Maps, Gmail, Workspace, Google Cloud, advertising platforms, devices, and Gemini AI products. The company develops large-scale computing infrastructure and research that power information retrieval, communication, productivity, media, navigation, and machine learning. Google is the largest operating business within Alphabet and earns a substantial share of its revenue from digital advertising.

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Job Overview
Eligibility
United States Right to work in the United States required.
Workplace
On-site
Job Posted:
1 day ago
Job Type
Full Time
Education
Bachelor Degree, or equivalent experience
Experience
8-9 years

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