Software Engineering Tech Lead Manager, Search Intelligence, Discover User Understanding

Google

Mountain View (CA)

On-site

USD 207,000 - 300,000

Full time

2 days ago
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Job summary

Google Mountain View, CA, USA is seeking a Software Engineering Manager to lead the Discover team responsible for token-based user modeling and scalable recommender systems. You will guide multi-team collaboration, align product strategy, and drive production-ready ML solutions at scale.

The role emphasizes both technical leadership and people management, with responsibilities spanning research ideas, design reviews, and end-to-end deployment across Google’s information retrieval and

Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development, including 5 years in machine learning, recommendation, personalization, ads or search quality.
  • 2 years of experience in a people management or team leadership role.
  • Experience training, evaluating, or launching models for recommender systems.
  • Experience with applied machine learning for recommendation, retrieval, or search platforms.

Responsibilities

  • Lead the Discover team owning interpretable token-based user models.
  • Set multi-quarter technical strategy and roadmap for token-based user modeling.
  • Oversee end-to-end model development from research ideas to production launches.

Skills

Software development experience
ML/recommender systems
People management
Model training/evaluation
Applied ML for recommender systems

Education

Bachelor’s degree or equivalent practical experience

Job description

Google Mountain View, CA, USA

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development, including 5 years in machine learning, recommendation, personalization, ads or search quality.
  • 2 years of experience in a people management or team leadership role.
  • Experience training, evaluating, or launching models for recommender systems.
  • Experience with applied machine learning for recommendation, retrieval, or search platforms.
Preferred qualifications:
  • Experience re-architecting production ML systems while maintaining downstream compatibility and stability.
  • Management experience, leading a team of 5 or more engineers.
  • Knowledge of modern recommender-system and ML techniques (e.g., user modeling, embedding-based and two-tower retrieval, sequence models and Transformers, distillation, multi-task and multi-objective learning, and applying LLMs to recommendation).
  • A track record of leading ML projects from design to launch that require coordinating multiple teams.
  • Excellent written and verbal communication, and the ability to align stakeholders with different priorities.
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. Discover User Modeling and Retrieval builds Google's foundational knowledge of what people care about, and uses it to power Discover. These models drive hundreds of billions of recommendations a day in Discover, are critical personalization signals in downstream ranking, and feed personalization across Google, including Search Suggest, News, Search notifications and Shopping. You will lead the team that owns Discover's interpretable, token-based user models, including Long-Term Interest and Creator models. These are the models that build the billions of interest profiles above, and the ones other Google products rely on. In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Manage and grow a team of engineers, mixing senior technical leads and early-career engineers, while developing each engineer's career and building a high-velocity team culture. Partner closely with DeepMind and Infra teams, and own our models end-to-end, from research ideas to production launches, at a scale few places can offer. Set and own the multi-quarter technical strategy and roadmap for token-based user modeling with the team's tech leads, product management, and partner teams. Drive the rebuild of interest-vocabulary redesign, unification of the token models, and the next-generation model architecture by making sound technical trade-offs and running thorough design reviews. Raise the bar on experimentation and evaluation by investing in offline evaluation that predicts online results (including LLM-based autoraters), faster iteration loops, and disciplined live-experiment and launch practices.

  • Partner closely with DeepMind and Infra teams, and own our models end-to-end, from research ideas to production launches, at a scale few places can offer.
  • Set and own the multi-quarter technical strategy and roadmap for token-based user modeling with the team's tech leads, product management, and partner teams.
  • Drive the rebuild of interest-vocabulary redesign, unification of the token models, and the next-generation model architecture by making sound technical trade-offs and running thorough design reviews.
  • Raise the bar on experimentation and evaluation by investing in offline evaluation that predicts online results (including LLM-based autoraters), faster iteration loops, and disciplined live-experiment and launch practices.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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