Machine Learning Architect

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