Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in Java and C .
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:- Master's degree or PhD in Computer Science or related technical field.
- 5 years of experience with data structures/algorithms.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
About the jobIn this role, you will help establish a framework for integrating rights-protected, premium data-such as e-books and subscription-based scholarly archives-directly into Google's generative AI products, including NotebookLM or Gemini Deep Research, to connect consumers with experts. You will help connect the platform to these launch surfaces.
This is a collaborative effort that spans teams within Google. You will work with various cross-functional groups across the company to unlock AI capabilities from premium content.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $253000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Design, build, and maintain robust, scalable software systems and infrastructure for information retrieval built on top of LLMs.
- Develop and iterate on algorithms and evaluation models to retrieve high-value content, which includes defining and extracting quality signals.
- Thrive in a fluid environment and successfully navigate the ambiguity inherent in a new, early-stage initiative.
- Work closely with other engineers, product managers, and research teams across Google (such as Notebook LM, Play Books, Core Data, and Search).
- Maintain standards for code quality, system reliability, engineering best practices, and documentation.
