Software Engineer III, Machine Learning (Recommendations, Rankings, and Predictions)

YouTube, a leader in video sharing and content discovery, is seeking a Software Engineer III specialized in Machine Learning to join their team in Mountain View. This role sits at the crucial intersection of AI and user experience, focusing on developing sophisticated recommendation, ranking, and prediction systems that shape how billions of users discover and interact with content.

The position offers an exciting opportunity to work on large-scale systems that directly impact how users explore and connect with content on one of the world's largest video platforms. You'll be part of a team that believes in giving everyone a voice and making the world better through shared stories and community building.

As a Machine Learning Software Engineer, you'll be responsible for developing and maintaining algorithms that power YouTube's recommendation and personalization systems. The role requires strong expertise in Python programming and machine learning, with experience in tools like TensorFlow. You'll work on complex problems involving large-scale data analysis, system design, and algorithm development.

The ideal candidate will have at least 2 years of experience in software development and machine learning, with a strong foundation in data structures and algorithms. You'll be expected to participate in design reviews, contribute to documentation, and collaborate with cross-functional teams to improve YouTube's recommendation systems.

This role offers competitive compensation, including a base salary range of $136,000-$200,000, plus bonus and equity opportunities. You'll be working at Google's Mountain View campus, contributing to technology that impacts billions of users while being part of a culture that values diversity, creativity, and innovation.

Join YouTube's engineering team to help shape the future of content discovery and user engagement, working with cutting-edge technology while solving real-world problems at massive scale. This is an opportunity to be part of a team that moves at the speed of culture and continuously pushes the boundaries of what's possible in content recommendation and personalization.