Devsinc

NLP Engineer - Arabic Language Focus

Riyadh, Saudi ArabiaPosted 5 months ago

Salary
AED 20k–34k a month· est.
Job type
Full time
Level
Mid level
Field
AI & Machine Learning
Work mode
On site

About the role

We are seeking an experienced NLP Engineer with strong expertise in Arabic Language Processing and Large Language Models (LLMs) to design, develop, and deploy intelligent AI solutions for Arabic and multilingual applications. The role involves building advanced NLP systems for chatbots, virtual assistants, intelligent search, document processing, and other AI-driven digital solutions. The ideal candidate will have hands-on experience in developing production-grade NLP models, implementing Retrieval-Augmented Generation (RAG) architectures, and deploying scalable AI services in cloud environments. Benefits - Medical Inpatient & Outpatient Facilities - Paid Overtime - Engaging Company Activities - Sports Allowance

Requirements

  • - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • - 3–6 years of experience in NLP, Machine Learning, or AI Engineering.
  • - Strong experience working with Arabic language NLP solutions.
  • - Proficiency in Python and modern NLP/ML frameworks.
  • Hands-on experience with:
  • - Transformers and Large Language Models (LLMs)
  • - Embeddings and Vector Search
  • - Tokenization
  • - Text Classification
  • - Named Entity Recognition (NER)
  • - Sentiment Analysis
  • - Text Summarization
  • - Retrieval-Augmented Generation (RAG)
  • - Proficiency in Python.
  • - Experience with Hugging Face, spaCy, and FastAPI.
  • - Experience implementing MLOps practices, including model deployment, monitoring, and lifecycle management.
  • - Experience deploying AI solutions on cloud platforms such as AWS, Azure, or GCP.
  • - Strong understanding of scalable AI architectures and production environments

Responsibilities

Design, develop, and deploy NLP models and AI solutions for Arabic and multilingual applications, including chatbots, virtual assistants, intelligent search, document processing, and other AI-driven digital solutions. Build production-grade NLP systems, implement Retrieval-Augmented Generation (RAG) architectures, and deploy scalable AI services in cloud environments.

Skills

  • Python
  • Transformers
  • Large Language Models (LLMs)
  • Embeddings
  • Vector Search
  • Tokenization
  • Text Classification
  • Named Entity Recognition (NER)
  • Sentiment Analysis
  • Text Summarization
  • Retrieval-Augmented Generation (RAG)
  • Hugging Face
  • spaCy
  • FastAPI
  • MLOps
  • Model deployment
  • Monitoring
  • Lifecycle management
  • AWS
  • Azure
  • GCP

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