Senior Staff Software Engineer, Google Cloud Storage Performance - Google
Sunnyvale, CA
About the Job
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development, and with data structures/algorithms.
- 5 years of experience with design and architecture; and testing/launching software products.
Preferred qualifications:
- Master's degree or PhD in Computer Engineering, Electrical Engineering, or Computer Science.
- Experience with OS and storage systems, with the ability to root cause performance issues.
- Experience with computer architecture, performance analysis, performance modeling, distributed systems, networking, queueing theory, and related software infrastructure.
- Excellent problem solving skills, with the ability to work across different teams across the hardware/software stack.
- Excellent collaboration and communication skills to drive cross-functional alignment and roadmap, as well as articulate and influence the strategies for key product areas.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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 define and drive strategic directions for storage platforms roadmap, cross-stack storage efficiency, and will work with leaders of platforms storage and infrastructure storage to establish methodology, tools, and programs for improving storage TCO, performance, reliability, fleet efficiency, and drive consensus among partner teams to advance storage platforms roadmap. You will also work with the technical team to provide guidance for storage NPI, storage analytics, and storage efficiency.You will work on new storage platforms and architecture to power Google Cloud workloads, analyze key performance issues with efficient exploitation of storage, HDD, NVM, networking, and I/O architecture to enable new capabilities, including performance evaluation, analysis, debugging, and optimization to ensure SSD performance on new server platforms.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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
- Collaborate with internal and external vendors on hardware/software co-design through performance analysis, evaluation, and optimizations.
- Evaluate and enable hardware features to benefit Google workloads.
- Develop tools and methodology to measure, evaluate, analyze, and improve Google infrastructure performance, TCO, and reliability.
- Identify infrastructure issues and devise software, hardware, or other solutions. Drive NPI of new systems with high standards for performance, power, cost and reliability.
- Build vendor relationships to influence and align priorities with Google's needs, support cross-team and cross-stack collaboration to uncover new opportunities, help product areas understand Performance/TCO tradeoffs for system design and deployment choices, and explore and apply innovative AI techniques for engineering productivity and performance optimization.
