Data & Applied Scientist - Microsoft Search, Assistant and Intelligence
Prague, Prague, Czech Republic
před 5 dny

Join the dynamic and exciting Microsoft Search Relevance team to deliver innovative, next-generation search and knowledge mining capabilities to a variety of applications & scenarios globally.

Our expert group of Software Engineers and Data & Applied Scientists leverage machine learning, artificial intelligence, and state-of-the-art technology to advance the relevance & applicability of search solutions over a variety of knowledge & information sources.

We are looking at a plethora of canvases to deliver intelligent, assistive search solutions in Office applications, or embedded in other Microsoft or 3rd party offerings.


  • Perform experiments with an understanding of ML algorithms and large-scale data mining.
  • Analyze challenging ML algorithms
  • Design & implement self-contained components as well as large, team-oriented code.
  • Review and develop code using the likes of C++, C#, Python
  • Engage in multiple simultaneous projects.
  • Required skills :

  • 2+ years research & development experience in at least one of the following areas is required : information retrieval, dialog systems, natural language processing or speech recognition systems, with a strong emphasis on machine learning.
  • Software design and development experience with C++ / C# / Java / Python
  • Strong verbal and written communication skills in English. Fluency in one or more other languages is highly desirable
  • Preferred Skills :

  • Experience with deep learning methods
  • Experienced in writing scalable, distributed and highly efficient components
  • The ideal candidate will have solid academic and / or corporate research background. Industry or other practical experience highly desirable.
  • Proven ability to independently conduct research and address issues ranging from fundamental algorithm development / implementation / optimization to driving eventual product outcomes.
  • Experience with distributed processing techniques such as Hadoop or Map / Reduce preferred.
  • Demonstrated experience delivering results through collaboration across disciplines, feature teams, and partners

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