Knowledge Engineer

Structuring and formalization of information, design and programming of cognitive systems (knowledge processing systems).
The specialist will need to develop a universal cognitive model of knowledge and a system for processing this knowledge (extraction, storage, search for knowledge, logical and statistical derivation of new knowledge)

General IT requirements:
- knowledge of Python3 / C ++ / Java;
- understanding of complex data structures;
- understanding and experience with SQL such queries;
- knowledge of basic network protocols and client-server architecture;
- Git experience;
- experience with SQL and No SQL databases (in particular with graph databases);
- Experience with microservice architectures.

General requirements for data analysis and big data:
- Experience with Machine Learning (techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision tree, clustering, artificial neural networks, etc.);
- Deep Learning experience;
- Experience of Natural Language Processing and in particular Information Extraction;
- experience in standard technologies of data science (PyTorch, Pandas, Keras, SciPy, SciKit, Tensorflow, NumPy, MatLab, etc.);
- Experience in creating data storage and processing architecture and knowledge (data architectures, data models, data warehouses / data lakes).

Knowledge Engineering Specific Requirements:
- experience with semantic web (SPARQL, Linkde data, RDF, OWL, SWRL, RuleML, etc.);
- experience with ontologies;
- experience and / or development of a knowledge storage system;
- development experience of logical inference systems
About the recuiter
Member since May 20, 2018
Desi Nur
from Ceara, Brazil

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