Deep learning via multi-layered neural networks are pushing the state-of-the-art forward for many machine learning applications in diverse domains. We are looking for a skilled data scientist to join our team to help us improve our core automation capabilities with the design, implementation, and analysis of deep learning architectures.
Create statistical and machine learning models in multiple technologies to support customers goals
Use Deep Learning to push forward the state-of-the-art in quality text and image processing for machine learning models
Apply Deep Learning to detect objects in real world contexts
Use Deep Learning to optimize large-scale machine learning algorithms with thousands of parameters
Design algorithms that combine human machine workers to train high quality ML models
Use our Virtual Data Scientist to create automatic hypotheses from your architectures.
Qualifications/Experience
Expert in machine learning (classification, clusterization and data mining)
Experience in usage of neural networks
Master's or PhD in a related field such as CS, Machine Learning, Statistics, Natural Language Processing (NLP), etc.
Excellent programming skills
Good knowledge of algorithms and data structures, for example, graph theory, theory of finite state automata, etc.
Experience in open source toolkits and libraries for machine learning
Strong foundation in machine learning including Probability Theory, Statistics, Big Data, etc.
The ability to think - out of the box- to combine multiple possibly unrelated solutions to solve a single complex problem
Any published journal and/or conference papers and completed project descriptions should be submitted with the application
Kaggle account with high stats or publication or PhD would be a huge plus