Staff Software Engineer, Google Cloud Storage
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
About the job
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.
Google Cloud Storage provides a suite of services like the scalable Google Cloud Storage (GCS) for unstructured data, high-performance managed lustre for AI High-Performance Computing workloads, and the managed Network File System (NFS) service filestore. These offerings are fundamental to Google Cloud's infrastructure, serving as the backbone for storing and accessing the vast datasets required for training and deploying AI models. In the AI era, this storage portfolio is crucial for enabling innovation, supporting compute-intensive tasks, and driving significant value for Google Cloud customers. The performance, scalability, and flexibility of these storage solutions are key to unlocking the potential of AI.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities
- Design and implementation of high-complexity features. Deliver robust, production-ready code for storage solutions that address the specific demands of AI/ML workloads.
- Architect scalable and performant storage solutions. Make data-driven decisions to optimize system efficiency and reliability.
- Provide deep-dive code reviews and technical guidance to the team. Set the standard for engineering excellence and help maintain a high quality bar for all deliverables that addresses the expectations of key Google customers.
- Identify and resolve performance bottlenecks and intricate system issues. Develop innovative, practical solutions to technical challenges that arise at the intersection of storage and ML.
- Partner with product and engineering stakeholders to translate customer requirements into technical specifications, ensuring the incubation’s output aligns with broader Google Cloud goals.
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