Software Engineer, Storage Analytics
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in software development, and with data structures/algorithms.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- Experience with software development in C++ and statistics.
- Experience with software development in C++, distributed computing and statistical analysis.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 3 years of experience testing, maintaining, or launching software products.
- Experience applying statistics and machine learning to large data problems.
- Experience with distributed systems.
- Excellent problem framing and collaboration skills.
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.
Storage-Analytics is a team of data scientists, software engineers, and researcher scientists, working at the intersection of Infrastructure-Storage and UFO. We work to optimize systems through resource abstraction, policy direction, system simplification, and algorithmic optimizations.
We work closely with the Storage Dev, SRE, and TPM teams on many strategic and tactical projects which sometimes venture up the stack to work with higher level systems and users. Team projects include optimizing predictive algorithms, creation and deployment of an abstracted IO unit, jointly reducing byte and IO stranding through colossus placement, designing a logging system that samples across different locality, prioritizing upgrades of network and machines, metric development that feeds to parms and finance, provide long term direction about the types of hardware we build.
Responsibilities
- Work with Engineering partners, and within the Analytics team (across NYC and SVL), and strategic and tactical optimizations to the storage systems.
- Work with complex data sets, and perform non-standard analysis.
- Build probabilistic models of our systems, compare those models with production to identify opportunities and communicate understanding.
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