招聘
About the job
YouTube Shorts is not just a product; it is a global engine for expression. The Creator Growth team is the vital heart of this ecosystem, responsible for inspiring over a billion viewers.
As the Principal Engineer you will grow content creation and build a sustainable ecosystem where millions of creators—from the newcomer to the established professional—find their audience and their voice. You will be responsible for the technical strategy that ensures a healthy supply of high-value content. You will solve large-scale machine learning challenges that define the next era of discovery for creation growth.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.
The US base salary range for this full-time position is $307,000-$427,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
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Grow the creator ecosystem by inspiring viewers to create.
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Model the sparse and complex Consumption to Creation (C2C) journeys to understand what truly inspires Shorts viewers to create. Build attribution systems that track inspiration sources over multiple touch points.
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Build cold-start solutions to match creators with their audiences. Lead the shift from views-only rewards to sophisticated deeper engagement and creator recognition value models.
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Leverage LLMs, multi-modality modeling, and large embedding models to build specialized recommender systems that understand content at a granular level. Partner with Gemini and Research teams to integrate state-of-the-art tools that lower the barrier to entry for billions of potential creators.
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Partner with CoreX, Music, Community, and Infrastructure teams, ensuring the creator growth vision is integrated across the YouTube stack.
Minimum qualifications
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Bachelor's degree in Engineering, Computer Science, or equivalent practical experience.
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15 years of experience in engineering.
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Experience with cross-functional technical innovation.
Preferred qualifications
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7 years of experience in a technical leadership role responsible for multiple technical areas and setting technical direction.
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Ability to manage multiple complex assignments simultaneously and work with geographically dispersed, cross-functional teams.
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Deep expertise in large-scale recommendation systems (retrieval/ranking), Generative AI for content understanding, and machine learning infrastructure.
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关于Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
员工数
Mountain View
总部位置
$1,700B
企业估值
评价
3.7
25条评价
工作生活平衡
3.8
薪酬
4.2
企业文化
3.4
职业发展
3.9
管理层
2.8
68%
推荐给朋友
优点
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
缺点
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
薪资范围
57,502个数据点
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0份报告
$176,704
年薪总额
基本工资
-
股票
-
奖金
-
$150,298
$203,110
面试经验
9次面试
难度
3.4
/ 5
时长
14-28周
录用率
44%
体验
正面 0%
中性 56%
负面 44%
面试流程
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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