Software Engineer III, Search, AI/ML
Description
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: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
- Design, implement, and maintain robust, well-tested software across the entire development lifecycle to mitigate a full range of external and internal access-related security risks within Search.
- Contribute to the codebase by authoring technical design documents, participating in code reviews, and driving debugging and testing efforts to ensure high system reliability.
- Translate the team's high-level goals into actionable tasks, and align your daily work with quarterly objective and key results (OKRs) to deliver on project milestones alongside peer engineers, T/PgMs, and other stakeholders.
- Foster a collaborative, and safe environment by communicating effectively and supporting your peers, while bringing the AI fluency expected to your daily engineering workflows.
- AI fluency is an expectation in this role. Be prepared to discuss your knowledge and use of AI tools during the hiring process.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in C++.
- Experience in designing, building, or operating large-scale distributed systems.
- Experience in software architecture, system design, and full-cycle software implementations.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience in data privacy, data protection, or secure data handling practices.
- Experience in policy compliance, regulatory frameworks, or governance.'
- Experience in database querying, data extraction, and analysis using SQL.
- Experience in log analysis, system monitoring, and technical troubleshooting in large-scale or distributed environments.