Required ML Engineer.
Follow software engineering, agile methodologies and data engineering best practices.
Be a major contributor in shaping our engineering practices, innovation and culture.
Work closely with other teams to help create new, innovative, NLP/ML solutions.
Work with our Knowledge Engineering and Product teams to define requirements and translate those into well designed algorithmic research and solid software solutions.
Keep up to date with trends and new technologies & processes
Work in an agile environment fast research, development and deployment cycles enabling immediate feedback from our Knowledge Engineering teams.
Requirements:
M.Sc. or higher in Computer Science / Statistics / Mathematics.
At least 5 years experience of software design and development, implementing algorithm-based solution frameworks that are extensible, robust, scalable and high-performance.
Proven knowledge of statistical NLP / Machine learning techniques for processing textual content to provide topic modeling, named entity recognition, sentiment analysis, clustering, classification.
Semantic Modeling technologies (Taxonomies, Ontologies, Knowledge Graphs, RDF, OWL, SPARQL)
Strong Python/Java/Scala Development skills with the ability of developing large scale solution frameworks
Experience with Python/Java ML/NLP packages and tools (Stanford CoreNLP, Gate, Apache Mahout, Spark ML/NLP, Spacy, etc.)
Huge advantage - At least 3 years experience in research and development of statistical NLP solutions in the industry, from conception to full production code.