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ML Engineer - NLP

Full-time

Entefy

If you’re fluent in natural language processing, you may be the hyper-talented Machine Learning Engineer that’s going to help Entefy rewrite the code of human communication.

We are looking for a talented and driven NLP specialist to join a high-impact team at the core of Entefy’s mission. You will use deep learning and other methods to work on confidential projects that will impact Entefy’s suite of products. This is highly challenging work that will engage your deep understanding of algorithms to build never-before-seen machine intelligence.

Requirements:

  • Solid fundamentals in mathematics, statistics, and machine learning theory

  • Minimum 3 years of commercial experience (or equivalent) in natural language processing, understanding, or generation

  • Demonstrable proficiency in at least one programming language such as Python, C, C++, Java, etc.

  • Proficient knowledge of and experience with text analytics, knowledge base construction, machine translation, or dialog systems

  • Proficiency in natural language processing tools such as NLTK, CoreNLP, Gensim, spaCy, OpenNLP, UIMA, GATE, etc.

  • Proficiency in machine learning tools such as TensorFlow, Keras, Caffe, Theano, MLLib, Torch, etc.

  • English fluency

  • Excellent written and verbal communication skills

Other qualifications:

  • Experience with modern deep learning techniques in NLP including sequence to sequence models, distributed representations, pointer networks, attentional models, etc.

  • Advanced degree in Computer Science, Machine Learning, Mathematics, Statistics, Physics, or Computational Linguistics

  • Experience with text-based information retrieval technologies such as Lucene, Solr, Elasticsearch, etc.

  • Experience with big data and distributed computing technologies such as Hadoop, MapReduce, Spark, Storm, etc.

  • Fluency in multiple languages is a plus

  • Demonstrable proficiency in more than one applicable programming languages is a plus

Visit and

Vacancy posted 17 days ago
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