About the job
We do research differently here at Google. Our team of Research Scientists are embedded throughout the engineering organization allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, Research Scientists work on problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. Research Scientists work closely with Software Engineers to discover, invent and build at the largest scale. Ideas may come from internal projects as well as from collaborations with researchers at partner universities and technical institutes all over the world. As a Google Research Scientist, you'll continue to be an active contributor to the wider research community by collaborating with academic researchers and by publishing papers, open source projects and web articles to communicate research findings.
Researchers on the Google AI team have the freedom to set their research agenda and to engage as much or as little as they wish with existing products, choosing between doing more basic, methodological research or more applied research as necessary to produce the most compelling results. Because many of the advances we develop today may take years to become useful, the team as a whole maintains a portfolio of projects across this spectrum. It is our philosophy that making substantive progress on hard applications can help to drive and sharpen the research questions we study, and in turn scientific breakthroughs can spawn entirely new applications.
The Google AI teams research focuses on methods that can learn multiple layers of rich, non-linear feature extractors and can scale to large amounts of data. Much of our work is best understood as part of the 'deep learning' subfield of machine learning, but we are interested in any methods such as evolutionary computing, novelty search or reinforcement learning that advance the capabilities of machine intelligence. We have resources and access to projects impossible to find elsewhere.
There is always more information out there, and the Research and Machine Intelligence team has a never-ending quest to find it and make it accessible. We're constantly refining our signature search engine to provide better results, and developing offerings like Google Instant, Google Voice Search and Google Image Search to make it faster and more engaging. We're providing users around the world with great search results every day, but at Google, great just isn't good enough. We're just getting started.
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