Technical Lead, YouTube Posts Discovery, Machine Learning and Recommendation

Role Overview

The new Posts Discovery team will be directly responsible for Posts growth and quality efforts. Posts are a new fast-growing content format on YouTube used by creators to share text, images, polls, quizzes and are already enjoyed by 300M+ daily engaged users. Our team is responsible for recommending posts safely across the entire YouTube ecosystem, including YouTube’s Home page, Shorts Feed, WatchNext, Search, Notifications, and dedicated vertical experiences such as News. In short, we aim to serve appropriate posts to the appropriate users at an appropriate time.

In the next couple years, the team’s mission is to grow Posts as a primary content on YouTube via widely expanded recommendation and a dedicated Posts Feed with monetization, incentivize and inspire high quality Posts creation, and ultimately drive more YouTube visits via Posts recommendation.

Responsibilities

• Define technical strategy and solutions for enhancing YouTube Posts discovery models and systems to accelerate viewer and creator growth while improving user satisfaction.
• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables. Design, develop, test, and deploy large-scale recommendation models, novel model architectures, and optimize ML infrastructure to drive the growth of the Posts ecosystem.
• Partner with engineering, product, data-science to convert business goals into scalable technical solutions that grow the Posts ecosystem.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach engineers on the team.
• Lead and mentor a team of engineers.

Requirements & Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience in software development.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• Experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and building architecture in different modeling domains.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• Experience with one or more of the following: large-scale recommendation or search systems, reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• Experience in people management, or interest in developing into a people manager.
• Experience of applying machine learning to improve user recommendations through fast experimentation and metric-driven iterations.

Application Instructions

Apply directly on Google Careers at Technical Lead, YouTube Posts Discovery, Machine Learning and Recommendation↗.

Direct application sign-in: Submit Application↗

Note: In most instances, this position requires in-person interviews as part of the hiring process.