Machine Learning Architect Responsibilities 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. 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 Spark ML/Hadoop, Yarn, kubernetes, AWS ECS Excellent understanding of algorithms and data structures for optimization. Have 5 years design/implementation/consulting experience of Machine Learning/AI/Deep Learning solutions. Understanding of network would be an asset. Fluent in Mandarin.
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Machine Learning Architect
Responsibilities
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.
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 Spark ML/Hadoop, Yarn,
kubernetes, AWS ECS
Excellent understanding of algorithms and data structures for optimization.
Have 5 years design/implementation/consulting experience of Machine Learning/AI/Deep Learning solutions.
Understanding of network would be an asset.
Fluent in Mandarin.