Software Engineering Manager II, YouTube Posts Discovery
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Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
- Experience with machine learning development or software architecture.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience applying machine learning to improve user recommendations through fast experimentation and metric-driven iterations.
- Experience collaborating with cross-functional partners and managing technical relationships across organizations.
- Experience navigating large-scale engineering systems to deliver sustainable integration strategies.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
YouTube's Community Intelligence team leads machine learning efforts across YouTube Community products, including Posts, Comments, Fan Communities, Connections, Hashtags, and emerging GenAI initiatives. Within Community Discovery, the new Posts Discovery team is directly responsible for Posts growth and quality efforts.
As a Software Engineering Manager for the Posts Discovery team, you will lead and manage a team working across applied machine learning recommendations and drive Posts Feed growth and quality. You will develop a technical understanding of search and discovery systems to guide engineering priorities. In this role, you will partner with YouTube CoreX leads, balancing your team’s mission with YouTube’s overarching goals.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead and grow a team of software engineers focused on Posts recommendation systems on YouTube.
- Partner closely with cross-functional partners, product experience teams, CoreX and Shorts discovery teams, research and infrastructure groups, and other applied machine learning teams across YouTube to drive the team's vision and roadmap.
- Partner closely with senior technical leads on planning and coordinating project execution to grow Posts as primary content in YouTube.
- Empower high-value discovery of Posts through innovative recommendations and modeling technologies.
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