Staff Software Engineer, YouTube Discovery Data

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development,
  and with data structures/algorithms.
  
• 5 years of experience testing and launching software products, and 3 years of experience with software design and architecture.
  
• 5 years of experience with Big Data technologies, analytic warehousing technologies, data processing technologies, and performance and scalability optimizations.
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 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.
  
• Experience in Data collection/monitoring/alerting infrastructure, data analysis pipelines, and machine learning.
  
• Excellent coding skill in C++, Java or Python.

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

The YouTube Discovery Data team is responsible for the data that powers personalized discovery at YouTube -- the YouTube homepage, watch page, and dozens of other surfaces that allow users to discover content on YouTube. Engineers across YouTube and Google use our data to directly power recommendation systems, to build ML models and user models, to analyze user behavior and evaluate experiments, to build user facing features, and to serve great personalized ads.

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 $189,000-$284,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. 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

• Develop infrastructure for longitudinal user data on woodshed to power sequence model training for dozens of ML models in YouTube.
  
• Build new features for session-based training data Woodshed to improve YouTube’s nomination and ranking models.
  
• Stream data for ML model training to improve freshness of YouTube recommendations.