Research in machine intelligence has already impacted user-facing services across Google including Search, Maps and Google Now. Google Research & Machine Intelligence teams are actively pursuing the next generation of intelligent systems for application to even more Google products. To achieve this, we’re working on projects that utilize the latest techniques in Machine Learning (including Deep Learning approaches like Google Brain) and Natural Language Understanding.
We’ve already been joined by some of the best minds, and we’re looking for talented Research Scientists that have appliedexperience in the fields of Machine Learning, Natural Language Processing and Machine Intelligence to join our team.
We do research differently here at Google. Research Scientists aren't cloistered in the lab, but instead they 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 research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, Research Scientists and Software Engineers work on challenges in machine perception, data mining, machine learning, and natural language understanding. You stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
There is always more information out there, and Research and Machine Intelligence teams have 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.
- Participate in cutting edge research in machine intelligence and machine learning applications.
- Develop solutions for real world, large scale problems.
- PhD in Computer Science, related technical field or equivalent practical experience.
- Programming experience in one or more of the following: C, C++ and/or Python.
- Experience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence).
- Contribution to research communities and/or efforts, including publishing papers at conferences such as NIPS, ICML, ACL, CVPR, etc.
- Relevant work experience, including experience working within the industry or as a researcher in a lab.
- Ability to design and execute on research agenda.
- Strong publication record.