NetBrain Technologies

  • Machine Learning Architect

    Job Locations US-MA-Burlington | CA-ON-Toronto
    Category
    Network Engineering
    Type
    Regular Full-Time
  • Company Summary

    best happy.netbrainers (2)

     

     

    Founded in 2004, NetBrain is the market leader disrupting the network automation space. Its ground-breaking automation platform leverages the power of dynamic maps to provide CIOs and network teams with end-to-end network visibility while enabling adaptive automation across the organization’s physical, virtual and software-defined networks. Today, over 2,000 of the world’s largest enterprises and managed services providers leverage NetBrain’s platform to automate network documentation, troubleshooting, and change management. 

     

    “NetBrain’s success is due to our people, and over the years, we have been fortunate to attract top talent because of our unique culture and exciting mission to transform the network management industry.” - Lingping Gao, Chairman and Chief Executive Officer of NetBrain

     

    GROW WITH US!

    Overview

    Responsible for building Machine Learning architecture and solutions to maximize the interpretation of our data in order to provide reliable predictive models.
    Provide insight of network data and solve complicated network problems with Machine Learning, Data Mining or Statistical Inference techniques.
    Design, document and lead the implementation of software and systems to help ensure optimal implementation of the neural network models, real-time analytics with enterprise data.

    Responsibilities

    Architect machine learning solution to solve network problems and productionize research
    Help establish machine learning workflow

    Qualifications

    Master Degree in Machine Learning, Data Mining, Statistical Inference, Mathematical modeling or similar fields with 5 years of industrial experience or Ph.D degree in Computer Science or related quantitative field

    5+ years of experience in machine learning and data science
    Experience in the following areas: supervised and unsupervised learning, large-scale data mining, NLP, anomaly detection
    Excellent understanding of machine learning techniques and algorithms
    Deep understanding of statistics and probability
    Proficiency with Python
    Experience with machine learning packages such as TensorFlow, Theano, Keras, Pandas, NumPy, scikit-learn
    Experience resolve any domain problem using Machine learning technology
    Experience with distributed computing frameworks Yarn, kubernetes, AWS, Spark, Hadoop
    Excellent understanding of algorithms and data structures for optimization

    Options

    Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
    Share on your newsfeed