NetBrain Technologies

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Machine Learning Architect

Machine Learning Architect

Job Locations 
US-MA-Burlington
Category 
Network Engineering
Type 
Regular Full-Time

More information about this job

Company Summary

NetBrain is the market leader disrupting the network automation space. Our 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 1,800 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

 

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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

Help team to research and build mathematical model for real network problems.
Transfer research result into industrial product/solution.
Help to build team and establish the workflow.
Mentor other data scientists in algorithms, models, tools, and products that make the team more efficient.

Qualifications

Master Degree in Machine Learning, Data Mining, Statistical Inference, Mathematical modeling or similar fields with 5 years of relevant experience or Ph.D degree in Computer Science or related quantitative field.
Experience in the following areas: machine learning, large-scale data mining.
Excellent understanding of machine learning techniques and algorithms.
Deep understanding of statistics and probability.
Proficiency with Python.
Experience with deep learning frameworks such as TensorFlow, Theano, Keras, Pandas, NumPy, scikit-learn.
Experience resolve any domain problem use Machine learning technology.
Experience with distributed computing frameworks Yarn, kubernetes, AWS ECS
Experience with Spark ML/Hadoop
Excellent understanding of algorithms and data structures for optimization.
Have 5 years of experience in Machine Learning field.