Software Engineer ll, Visual Query, Search

About the job

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.

A way to contribute to the multimodal world understanding frontier used by more then one billion users by contribution to the user-facing quality component by directly tuning Gemini models and handling any necessary engineering around.

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.

Responsibilities

• Execute quality improvements in the whole LLM life-cycle, analyze headroom, prototype, prompt engineer, collect data, train, eval, iterate/repeat.
• Write high quality code (colab, C++ pipelines, Kotlin) at high velocity to integrate quality components within next generation of Search infrastructure (e.g., Mars).
• Find simple solutions to hard problems in constantly changing environment.
• Focus on delivering quality impact on metrics in offline evals (human evals, autoraters) and live traffic.