Drimva

Google

Tech Lead, YouTube Shorts Discovery, ML Recommendations

Mountain View, CA, USA · Full-time · Posted Oct 12, 2026

Experience
8 years in software development; 5 years testing and launching software products; 3 years in software design and architecture; 5 years in speech/audio, reinforcement learning, or another ML field; 5 years in ML design and ML infrastructure. Preferred: 8 years in data structures and algorithms; 3 years in a technical leadership role.
Education
Bachelor’s degree or equivalent practical experience.

About the job

Lead engineering for YouTube Shorts discovery and recommendations, building ML-based systems that find initial audiences for fresh videos and personalize recommendations.

What you'll do

  • Provide technical leadership on high-impact projects, manage priorities and deliverables, and align teams on goals and timelines.
  • Lead design and implementation in specialized ML areas, optimize ML infrastructure, and guide model optimization and data processing strategies.
  • Design, develop, test, deploy, maintain, and enhance large-scale software solutions.

What they ask for

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development; 5 years testing and launching software products; and 3 years in software design and architecture.
  • 5 years of experience in speech/audio, reinforcement learning, or another ML field.
  • 5 years of experience with ML design and ML infrastructure, such as model deployment, evaluation, data processing, debugging, or fine tuning.

Nice to have

  • Master’s degree or PhD in a related technical field; 8 years in data structures and algorithms with experience building distributed, large-scale machine learning systems.
  • Experience designing and deploying recommendation, personalized ranking, or retrieval systems; expertise in cold-start, reinforcement learning, or exploration/exploitation algorithms.

Pay

$207000 - $300000 (USD) (base salary)

Tools

ML, LLM

AI focus

Build and improve personalized recommendations, LLM-based recommendation systems, discovery engines, and ML infrastructure for YouTube Shorts.

Model-written summary · the original posting is authoritative

First seen Oct 21, 2026 · Last verified Nov 5, 2026 (UTC)