YouTube, a leading platform in video sharing and community building, is seeking a Staff Software Engineer specializing in Machine Learning. This role represents a unique opportunity to work at the intersection of cutting-edge technology and creative expression, where you'll help shape how billions of users connect and share their stories worldwide.
As a Staff Software Engineer, you'll be working on critical projects that leverage machine learning algorithms and artificial intelligence to enhance the YouTube platform. The role requires a blend of deep technical expertise in software development, machine learning, and system architecture, along with leadership capabilities to drive technical direction and mentor team members.
The position offers an attractive compensation package ranging from $189,000 to $284,000, plus bonus, equity, and comprehensive benefits. Based in either New York City or Mountain View, you'll be part of a dynamic environment that values innovation and technical excellence.
Key responsibilities include writing system development code, leading design reviews, ensuring best practices through code reviews, and contributing to technical documentation. You'll work with cutting-edge ML tools and technologies, solving complex problems at scale while collaborating with cross-functional teams.
The ideal candidate brings 8+ years of software development experience, with particular expertise in machine learning algorithms, AI, and deep learning. You'll need strong leadership skills and the ability to work effectively in a complex, matrixed organization. This role offers the opportunity to make a significant impact on how billions of users experience YouTube while working with some of the most advanced technologies in the industry.
Join YouTube's engineering team to be part of a mission to give everyone a voice and show people the world. You'll work in an environment that combines technical challenges with creative expression, all while helping to build and maintain one of the world's largest and most influential platforms for content sharing and community building.