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What is it like to work at Google?
Working at Google means solving fascinating problems and making a positive difference in tens of millions of lives every day. This work has opened up interesting new areas for us and presented challenges that are not only new to us, but new to everyone in computing. These new problems require exceptional thinking and technical expertise to solve, but their solutions could dramatically improve the accessibility of information for everyone in the world. Here's a sampling of the kinds of things we work on at Google:
Large-scale computer systems problems, such as:
Designing and improving software that can crawl and index billions of web pages and other documents, comprising 20+ TB of raw data, in a few days.
Developing efficient implementations for large-scale mathematical problems, such as running Google's Pagerank™ algorithm on a graph of 3 billion nodes and 20 billion edges.
Developing algorithms and heuristics to keep our index up to the minute by finding and reindexing almost all web pages within minutes of when they change or they are created.
Efficiently and rapidly searching our full index of more than 2 billion web pages more than 150 million times per day (i.e. more than three thousand queries per second at peak traffic times), plus providing search over our archives of 20 years of Usenet data (700M+ messages) and 320M+ images.
Harnessing the computational resources of our more than 10,000 computers to solve large-scale problems (e.g. not just indexing documents but experimenting with new ranking algorithms, running machine learning algorithms on terabytes of data, etc.)
Using millions of computers to solve important problems requiring substantial CPU resources, such as cancer and disease research. For example, we have recently begun small-scale tests with the Folding at Home project at Stanford University with a few thousand selected Google Toolbar users, in preparation for a much larger scale system that would enable our millions of Google Toolbar users to opt-in to contributing their CPU cycles to solving important problems.
Building large-scale distributed file systems and other infrastructure that makes it possible to reliably and efficiently manage and process hundreds of terabytes of information.
Dealing with low-level networking issues as we crawl the web and serve user requests.
Developing Google's Search Appliance product, consisting of custom hardware and software for deploying Google's technology for searching private content.
