Machine learning Python developer

PROJECT DESCRIPTION
Given the increased interest in machine learning in all existing markets a need for customized neural networks has emerged. In collaboration with one of the biggest document scanning and processing company in Belgium we have decided to build a machine learning platform that would allow any interested party to build, test and deploy a neural network using their own data.
The purpose of the platform is to provide standard neural networks but most importantly to allow any company or individual to build, test and deploy their own custom neural networks. Because building a new neural network has a very steep learning curve for anyone not into the machine learning business our customers will have the ability to access our knowledge and request our help in building the needed network. That’s where you come into play.

JOB DESCRIPTION
Nenos Software is looking for a python developer to join the team that will build the next big thing. We need a versatile python developer with an inclination to mathematics that would love to help develop tools to build innovative neural networks for challenging real-world problems.
You would be helping with the analysis of existing models, building new and more efficient models and creating tools for interacting with models on a daily basis.
The current job opening is addressed mostly to developers that would like to make an impact in the world of machine learning and apply mathematics knowledge on problems that affect our customers on a daily basis.

KEY REPONSIBILITIES
• Build tools to improve productivity while working with models and interacting with our in-house data scientist
• Use machine learning libraries to automate the training and deployment of machine learning projects
• Build processes to export, deploy and maintain machine translation models; use cutting edge technology to improve the deployment process

REQUIRED SKILLS
• Good to strong knowledge of Python and Linux internals
• Understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Logistic Regression, XGBoost, etc.
• Background in one or more of : Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
• Experience using one of TensorFlow, MXNet, Theano, Caffe and other open source frameworks. Solid understanding of underlying concepts of Tensor Flow (as an example) to understand/enhance the inner workings of an AI framework of choice.