Software Engineer III, AI/ML, Google Cloud Storage
Google Cloud Storage (GCS) builds a planet-scale distributed storage system that manages exabytes of data for global enterprises, startups, and Google's core services (like Drive, Gmail, and YouTube).
As a Software Engineer, you will drive the GCS Autonomous Storage Management charter by building Agentic AI solutions. Collaborating closely with Product Managers and Technical Leads, you will design and build the core architecture of AI products that efficiently manage billions of cloud objects, ensuring a seamless, highly accurate, and reliable experience for cloud operators.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
- Write product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Design and build intelligent Storage AI Agents that automate customer storage management tasks, automatically tag data to assist AI researchers, and drive ongoing GenAI accuracy and security improvements.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages such as C++, Golang, Java, or 1 year of experience with an advanced degree.
- Experience with large-scale distributed infrastructure systems.
- Experience with AI/ML systems in a customer facing production environment.
- Experience in Generative AI (e.g., large language models, multi-modal, model training and evaluation).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies or cloud storage.
- Experience in Google technologies and platforms.
- Experience building high-volume data pipelines and resolving complex system scalability bottlenecks.
- Ability to troubleshoot and mitigate production incidents under strict service level agreements (SLAs) to minimize customer impact.
- Passionate about enterprise products, with a focus on growing our Cloud offerings in the space.