Senior Engineering Manager, YouTube, Recommendations ML

Google LLC; San Bruno (CA); On-site; USD 262,000 - 364,000; Full time

Benefits offered by this job

Equity

Bonus target

Comprehensive benefits

Job summary

Google LLC in Mountain View, CA is seeking a Software Engineering Manager to lead teams across information retrieval, AI, NLP, and large-scale system design. You will guide ML-driven recommender projects, align cross-functional roadmaps, and mentor engineers to optimize both code and processes.

Responsibilities include setting team priorities, guiding technical strategy, and overseeing deployment of large-scale ML models across multiple sites.

Qualifications

• 8 years designing and building large-scale ML models.
• 8 years launching software products with experimentation and user data.
• 5 years leading teams and managing people.
• Experience aligning cross-organizational roadmaps across multiple teams.
• Experience with recommender systems research or applied research.

Responsibilities

• Set and communicate team priorities that support broader goals and align across squads.
• Coach engineers, define performance expectations, and drive development discussions.
• Develop long-term ML goals and roadmaps beyond current teams and adapt to future needs.
• Oversee system designs and review code to solve complex problems.
• Lead ML infrastructure optimization and advanced recommendation system work.

Skills

Leadership in ML systems

Recommender systems

Cross-functional collaboration

Team management

Large-scale ML models

Education

Bachelor's degree in Computer Science or related field

Master's degree or PhD preferred

Tools

Gemini-based LLMs

Semantic IDs

ML infrastructure

Job description

In most instances, this position requires in-person interviews as part of the hiring process. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Bruno, CA, USA.

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 8 years of experience designing and building large-scale machine learning models.
• 8 years of experience building, testing, maintaining, and launching software products that require running and analyzing experiments and working with user data.
• 5 years of experience in a people management, supervision/team leadership role.
• Experience creating and aligning cross-organizational technical roadmaps across multiple software engineering, research, product management, and data science teams.
• Experience conducting research or applied research on recommender systems models or in related areas (e.g., ranking, retrieval, or user).

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• Experience guiding research programs in relevant areas for small teams.
• Experience with hardware ML model ML, and framework co-design.
• Experience optimizing compute or hardware capacity.
• Publications in Recommender Systems, LLM’s, large model performance and efficiency.

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. In this role, you will guide large machine learning (ML) models for recommender systems. You would be expected to have solid expertise in machine learning technology and continue to develop and innovate in the areas of ranking, retrieval and large language models (LLM). Building such models, analyzing user data for gaps and opportunities and evaluation of model architectures at the intersection of model/hardware/infrastructure co-design for performance and efficiency are likely activities. You would likely focus on a workstream Google calls Large Recommender Models, involving using Semantic IDs and leveraging Gemini-based LLM models for especially difficult recommendation use cases. You would be involved in aligning research directions with cross-YouTube and cross-product area partners, and manage a small team. 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 + benefits

Responsibilities

Learn more about benefits at Google .

• 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 long-term technical goal and roadmap within, and often beyond, the scope of your teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
• Oversee systems designs within the scope of the broader area, and review product or system development code to solve ambiguous problems.
• 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 .