Engineering Manager, YouTube Posts Discovery

About the Job

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: $207000 - $301000 (USD) + 20% bonus target + bonus + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Lead, manage, and grow a team of software engineers focused on posts recommendation systems on YouTube.
• Collaborate with cross-functional partners, product experience teams, coreX and shorts discovery teams, research and infrastructure groups, and other applied ML teams across YouTube to drive the team's goal and roadmap.
• Co-ordinate with senior Team Leader (TLs) to plan and execute project delivery, growing Posts as primary content on YouTube and enabling high-value discovery through innovative recommendations and modeling technologies.
• Cultivate team culture and values by developing individuals and creating a collaborative and agile environment.

Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management role.
• 2 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 2 years of experience leading ML design or optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.