Senior Staff Engineer, YouTube AI/ML Recommendations, Predictions

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Bruno, CA, USA; Mountain View, CA, USA. Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience building ML or AI systems or products.
• 3 years of experience building and deploying recommendation systems models (e.g., retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.

Preferred qualifications

• PhD in Machine Learning or publications in related areas.
• 3 years of experience analyzing data, drawing conclusions from the logs and using ML to improve the product.
• Experience building recommendation or personalization systems specifically for media products (audio, video, etc.).

About the job

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 recommendation systems suggests videos that maximizes value to our viewers. We have cutting edge technology and ML based algorithms to retrieve and rank the best possible videos given the user context and preferences. Our recommendation stack is constantly evolving to keep up with the newest advancements in ML technology (e.g. transformers, foundation, Gemini models).

This role requires very deep knowledge of ML technologies (especially in the area of recommendations). You will be working on cutting edge algorithms and optimization techniques. Prior ML experience is mandatory. We are looking for a research background in the form of a PhD in ML or publications in ML or related technical fields (including Physics, Math, Operations Research, Optimization, etc.)

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 $262,000-$365,000 + 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

• Design, develop, test, deploy, maintain, and enhance large scale software solutions.
• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
• Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of advanced recommendation systems.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.