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Software Engineering Manager II, AI/ML Recommendations, Rankings, Predictions, YouTube

Remote · USA Full-time New today

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Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 2 years of experience leading ML design or optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 2 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
  • 2 years of experience in a technical leadership role.
  • 2 years of experience in a people management or team leadership role.

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.

About the job Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way. With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. 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 $197,000-$291,000 + 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

  • Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  • Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
  • Develop the mid-term technical vision and roadmap within the scope of your (often multiple) team(s). Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
  • Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
  • Lead the design and implementation of recommendation systems, optimize ML infrastructure, and guide the development of model architecture.

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