Tech Lead, YouTube Shorts Discovery, ML Recommendations

About the role

The Short-form Video Exploration team manages the entire ecosystem: from mobile creation tools and effects (text, stickers, filters) to a seamless, full-screen player experience. We also build the backend systems required to create, serve, and recommend these videos across Home, Search, and beyond. Shorts Exploration is a critical component of our recommendation strategy.

Responsibilities

• Design, develop, test, deploy, maintain, and enhance large scale software solutions.
• Provide technical leadership on high-impact projects.
• Manage project priorities, deadlines, and deliverables.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines.
• Influence and coach a distributed team of engineers.
• Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.

Requirements

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products.
• 3 years of experience with software design and architecture.
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications

• Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field.
• 8 years of experience in data structures and algorithms, with experience building distributed, large-scale machine learning systems.
• 3 years of experience in a technical leadership role, defining technical goals, setting roadmap direction, and mentoring executive engineering teams.
• Experience designing and deploying recommendation systems, personalized ranking models, or retrieval systems.
• Expertise in managing the cold-start problem, reinforcement learning, or exploration/exploitation algorithms.

Skills

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Benefits

Learn more about benefits at Google.