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 this role, you will deliver high-quality, fresh web and social content for user journeys on Google Search. You will be a power key Search Results Page (SRP) features like Top Stories and the News Tab, and enrich Artificial Intelligence (AI)-driven experiences such as Artificial Intelligence (AI) Overviews (AIO) and Artificial Intelligence (AI) Mode (AIM).
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.
The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about
benefits at Google.
Responsibilities
- Collaborate closely with Indexing, Frontend, and Product Management partners on system development and launches.
- Conduct feature engineering to improve signals for content understanding and ranking.
- Optimize ranking performance against user, ecosystem, and quality metrics while iterating on quality using experiments, human evaluations, and automated rating systems.
- Experiment with and deploy advanced document and query understanding signals.
- Implement solutions in one or more specialized machine learning (ML) areas, utilize ML infrastructure, and contribute to model optimization and data processing.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in C++ programming languages, or 1 year of experience with an advanced degree.
- 2 years of experience analyzing data through statistical, quantitative modeling and forecasting.
- 2 years of experience designing, implementing, and optimizing advanced algorithms.
- 1 year of experience with one or more of the following: Natural Language Processing, reinforcement learning (e.g., sequential decision making), ranking, ML infrastructure, or specialization in another ML field.
- 1 year 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 a related technical field.
- 2 years of experience with data structures and algorithms.
- Experience with frameworks and tools relevant to AI/ML development and deployment, including proficiency in Python.
- Experience in designing and refining ranking algorithms or performing feature engineering for content understanding.
- Experience developing accessible technologies.
- Familiarity with search technologies, information retrieval, and natural language processing.