NLP Engineer

ITALY, Rome
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What would the job be?
Responsibilities:

As an NLP/ML Engineer, you'll work closely with our team to design, develop, and implement advanced NLP solutions. You'll be responsible for research, prototyping, and implementing various NLP and ML models to improve our product performance and quality.

You'll analyze complex datasets, develop state-of-the-art neural models, and collaborate with other developers to ensure project success.

Who are we looking for?
Requirements:
  • Master's degree (or near completion) in Computer Science, Computer Engineering, NLP, Data Science, ML, or a related field.
  • At least 1 year of NLP and ML experience, with a strong understanding of NLP and ML techniques, tools, and frameworks.
  • Proficiency in PyTorch and Python (Java knowledge a plus).
  • Excellent problem-solving skills, able to work independently and contribute to teamwork.

Desired:

  • Experience with cloud infrastructure and deployment using AWS, Azure, or Google Cloud Platform.
  • Experience with MySQL or PostgreSQL, ideally Elasticsearch.
  • Familiarity with natural language generation or conversational AI.
  • Strong communication and team-building skills.
Who we are
Babelscape is a deep tech company founded in 2016 focused on multilingual Natural Language Processing with the main goal of enabling multilinguality and text understanding in customers’ applications which deal with text in different ways. Thanks to technological transfer from the internationally renowned Natural Language Processing research group headed by prof. Roberto Navigli at the Sapienza University of Rome, winner of two European Research Council grants and of several international awards, we place ourselves on the market with very high professional profiles and the ability to tailor our solutions to the customers' needs.

The company's core mission is to overcome the language barriers by enabling the automatic processing of text independently of the input language, and distilling and aggregating the information extracted across languages by means of a unified large-scale multilingual knowledge repository and semantically-enhanced text comprehension systems.