Conduct in-depth loss analyses, data exploration, and prototyping to identify high-leverage opportunities and quality headroom across Factuality, Helpfulness, and Freshness.
Design and implement scalable systems, ranking formulations, ML scorers, and prompt/signal augmentations to improve input ranking and end-to-end context selection for AIO and AIM.
Evaluate the impact of context and ranking changes on both input-level metrics and downstream AI answer quality—driving changes from offline autorater evaluations through Live Experiments to full production launch.
Work across a wide breadth of systems spanning Google’s iconic core Search retrieval and ranking stack through modern AI answer quality, ML modeling, and serving infrastructure such as MaRS and Gemini/Magi orchestration and evaluation pipelines
Partner closely with Web Ranking, 1P Verticals, Serving Infrastructure, and LLM Modeling teams to align Search signals and context engineering with evolving Gemini capabilities.
Minimum qualifications:
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
Preferred qualifications:
Master's degree or PhD in Computer Science or related technical fields.
2 years of experience with data structures and algorithms.
Experience developing accessible technologies.
