About this role
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.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.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 1 year of experience with data structures and algorithms.
- 1 year of experience implementing core ML concepts.
- Experience integrating generative AI tools or LLM interfaces into workflows.
Preferred qualifications:
- Master's degree in Computer Science or related technical field.
- Conduct deep-dive 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 (Octopus), 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 (QRS, UberSearch, Tangram, Web Ranking) through modern AI answer quality, ML modeling, serving infrastructure such as MaRS and Gemini/Magi orchestration and evaluation pipelines.
- Partner closely with Web Ranking, first-party Verticals, Serving Infrastructure, and Large Language Model (LLM) Modeling teams to align Search signals.