Senior Staff Engineer, YouTube Shorts Ranking, Core Modeling

Bring ideas to optimize shorts feed for better user experiences, new use cases, and overall product quality.Build large-scale machine learning models, training infrastructure and quality evaluation, design ML architecture.Work with data scientists, product managers, front-end engineers, user experience designers to improve product quality.Minimum qualifications:Bachelor's degree or equivalent practical experience.8 years of experience in software development.7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).5 years of experience with design and architecture; and testing/launching software products.5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production.Experience building architecture in different modeling domains.Preferred qualifications:Master’s degree or PhD in Computer Science, Machine Learning, Computer Engineering, or a related highly technical field.8 years of experience with data structures and algorithms.5 years of experience in a technical leadership role leading project teams and setting technical direction.3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.YouTube Shorts is the short-form section of the video-sharing website YouTube, hosting content much like YouTube's primary service but with a focus on vertical videos at a maximum length of 60 seconds. For creators, it enables a space for content that is short, casual, and direct. Creators can try workshopping new material, share other videos on the platform, or provide a quick taste of their personality to prospective fans. For viewers, it provides high value in short intervals. Fans can easily access fresh, snackable content from their favorite creators, and discover new channels.We are building an entirely new experience for both creating videos and consuming them, for allowing creators to connect better with their viewers communities, from within the YouTube app.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: $262000 - $364000 (USD) + 25% bonus target + equity + benefitsLearn more about benefits at Google.Bachelor's degree or equivalent practical experience.8 years of experience in software development.7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).5 years of experience with design and architecture; and testing/launching software products.5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production.Experience building architecture in different modeling domains.