Minimum 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.
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.
Responsibilities- 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.
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
Learn more about benefits at Google .
