Join a dynamic team at the forefront of AI/ML specialized storage infrastructure, powering Google Cloud's critical business objectives. We develop high-scale systems tailored for the unique demands of AI and Machine Learning workloads.

Our GCSFuse product is dedicated to providing the most efficient and user-friendly file client for AI/ML workloads on GCP, experiencing rapid growth. We are now expanding our focus to achieve hyper-scale performance and deliver masterclass observability and debuggability.

Google Cloud empowers organizations globally to achieve digital transformation. We deliver enterprise-grade solutions leveraging Google's advanced technology, enabling developers to build more sustainably. Businesses worldwide rely on Google Cloud as a trusted partner for growth and resolving complex challenges.

Take ownership of your work area, designing and implementing projects spanning multiple quarters with minimal oversight. Develop expertise in your assigned domain and become a subject matter expert.

Identify and scope ambiguous problems, research innovative solutions and technologies, and propose recommendations that align with both immediate and long-term goals.

Lead technical direction and set priorities for small engineering teams (3-4 members), focusing on the design and implementation of complex features. Deliver robust, production-ready code for storage solutions that meet the specific needs of AI/ML workloads.

Serve as a key liaison for cross-functional partners, ensuring alignment on objectives and timelines with adjacent teams. Drive impact beyond your immediate role, influencing team members and other departments.

A Bachelor's degree or equivalent practical experience is required.

Possess at least 5 years of experience in software development across various programming languages.

Accumulate 3 years of experience in testing, maintaining, or launching software products, along with 1 year of dedicated experience in software design and architecture.

Demonstrate experience with file systems and a deep understanding of Linux kernel internals.