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NLP Engineer; Remote

Remote / Online - Candidates ideally in
Dubai, Dubai, UAE/Dubai
Listing for: Nybl
Remote/Work from Home position
Listed on 2026-01-02
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 120000 - 200000 AED Yearly AED 120000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: NLP Engineer (Remote)

About nybl

We are developing an ai ecosystem that enables businesses, in any industry, to deploy artificially intelligent solutions using both our platform and applications. Our technology allows anyone to build Ai solutions without writing a line of code or needing a degree in Data Science. Our ecosystem is world changing from healthcare to agriculture, education to industry, the applications of our technology are truly limitless.

We’re looking for a Natural Language Processing (NLP) Engineer to join our growing data science team. This is an exciting opportunity to work on cutting-edge projects, collaborate with a talented team, and see your work directly applied in production systems impacting millions of people.

Responsibilities
  • Assist in preprocessing and cleaning textual datasets
  • Implement basic NLP pipelines using libraries like NLTK, or Hugging Face
  • Design and implement NLP models for classification, entity recognition, and summarization
  • Fine-tune transformer-based models (e.g., BERT, RoBERTa) for domain-specific tasks
  • Familiarities with large language models and prompt engineering
  • Analyze model performance and iterate based on evaluation metrics
  • Contribute to scalable deployment of NLP services
Qualifications
  • Bachelor’s degree in Computer Science, with experience or specialization in NLP
  • Strong Python skills
  • Understanding of NLP tasks (tokenization, POS tagging, sentiment analysis)
  • Exposure to ML frameworks (e.g., Tensor Flow, PyTorch)
  • Experience with Hugging Face, Spa Cy, or Lang Chain
  • Minimum of 1–2 years of experience in NLP and LLMs modeling
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