Software Engineering Manager — Recommender & Search ML

Google LLC

Mountain View (CA)

On-site

USD 207,000 - 300,000

Full time

3 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 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

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