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

Google•Mountain View, CA

4d•$207,000 - $300,000

About The Position

The Software Engineering Tech Lead Manager will lead the team responsible for Discover’s interpretable, token-based user models, including Long-Term Interest and Creator models. These models build interest profiles that power Discover recommendations at very large scale and provide personalization signals to other Google products, including Search Suggest, News, Search notifications, and Shopping. The role combines technical leadership with people management. The manager will guide engineers, set technical strategy, and own models end-to-end from research ideas through production launch. The work includes partnering with DeepMind, Infrastructure teams, product management, and other partners to evolve user modeling and retrieval systems and support Google Search’s globally used products.

Requirements

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.

Nice To Haves

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, such as 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.

Responsibilities

Manage and grow a team of engineers, including senior technical leads and early-career engineers; develop team members’ careers and build a high-velocity team culture.
Partner closely with DeepMind and Infrastructure teams, and own models end-to-end from research ideas through production launches.
Set and own the multi-quarter technical strategy and roadmap for token-based user modeling in collaboration with the team’s tech leads, product management, and partner teams.
Drive the interest-vocabulary redesign, unification of token models, and development of the next-generation model architecture through sound technical trade-offs and thorough design reviews.
Improve 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.