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Ondřej Pacovský, Natural Language Processing (NLP) Developer in Prague, Czech Republic
Ondřej Pacovský

Natural Language Processing (NLP) Developer in Prague, Czech Republic

Member since April 16, 2018
Ondřej enjoys pushing the boundaries of artificial intelligence and making it useful for humanity. He has wide-ranging experience in artificial intelligence and machine learning, from being an individual contributor to leading teams and launching his own companies.
Ondřej is now available for hire

Portfolio

  • Eyen SE
    C++, CUDA, Python, NumPy, TensorFlow, Electron Microscopy, Machine Learning...
  • Google
    C++, Python, Java, BigTable, MapReduce, Large-scale Machine Learning...
  • Google
    Machine Learning, C++, MapReduce

Experience

  • C++, 15 years
  • Natural Language Processing (NLP), 10 years
  • Machine Learning, 10 years
  • Python, 7 years
  • NumPy, 6 years
  • Robotics, 5 years
  • Deep Learning, 3 years
  • Deep Neural Networks, 3 years
Prague, Czech Republic

Availability

Part-time

Preferred Environment

Tensorflow, Python/NumPy/Pandas, Linux, Git, C++

The most amazing...

...thing I've participated in is the Gmail Priority Inbox, saving time sifting through email for millions of users.

Employment

  • Co-founder, CEO, Chief Data Scientist

    2013 - PRESENT
    Eyen SE
    • Raised capital and put together an exceptional development team.
    • Developed a deep neural network-based system for automatically processing particles in micrographs from an electron microscope.
    • Implemented a correlation-based alignment method on GPUs, 100x faster than original NumPy/SciPy code.
    Technologies: C++, CUDA, Python, NumPy, TensorFlow, Electron Microscopy, Machine Learning, Deep Learning
  • Software Engineer

    2009 - 2013
    Google
    • Brought Priority Inbox from prototype to public launch.
    • Redesigned and prototyped a new learning back-end.
    • Managed Bigtable replication and load balancing across the globe.
    Technologies: C++, Python, Java, BigTable, MapReduce, Large-scale Machine Learning, Semantic Analysis
  • Software Engineering Intern

    2008 - 2008
    Google
    • Reduced the estimation error by 40% compared to handcrafted models.
    • Sped up the data acquisition library 10x for specific query types.
    Technologies: Machine Learning, C++, MapReduce
  • Lead Developer/AI Specialist

    2007 - 2007
    ALTAR Interactive
    • Led eight developers to deliver a successful, timely prototype.
    • Designed and implemented an AI module for the prototype.
    • Grew the team and introduced systematic development techniques.
    Technologies: C++, Python, SWIG

Experience

  • GMail Priority Inbox (Development)
    https://www.google.com/mail/help/priority-inbox.html

    Priority Inbox automatically identifies your important email and separates it out from everything else so you can focus on what really matters.

  • Eyen - Celine 3D Cryo-electron Microscopy Service (Development)
    http://www.eyen.eu

    Eyen is the expert in molecular imaging and nano-scale structural data analysis. Our expertise lies in advanced computational analysis of proteins, biologics, and nanoparticles for pharmaceutical research and development.

    Our unique 3D cryo-electron microscopy service supported by advanced algorithms provides outsourcing for your protein, biologics, and nanoparticle structural characterization needs quickly and with low up-front costs.

Skills

  • Languages

    Python, C++, Java, Prolog
  • Libraries/APIs

    NumPy, TensorFlow, OpenCV
  • Platforms

    Linux, CUDA
  • Storage

    BigTable
  • Other

    Deep Learning, Natural Language Processing (NLP), Word2vec, Machine Learning, Deep Neural Networks, Neural Networks, Computer Vision, Robotics
  • Tools

    Git
  • Paradigms

    GPGPU, MapReduce

Education

  • Master's degree in Theoretical Computer Science
    2000 - 2006
    Charles University - Prague
  • Master of Science degree (Distinction) in Evolutionary and Adaptive Systems
    2004 - 2005
    Sussex University - Brighton, UK
Certifications
  • Deep Learning Specialization
    NOVEMBER 2018 - PRESENT
    Coursera
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