LLM Engineer - Arabic Speaker
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Design, develop, and deploy Arabic-first Large Language Model (LLM) solutions to support AI-driven products and client projects, ensuring high-quality Arabic language understanding, generation, and contextual accuracy across enterprises.
Key Responsibilities
1. LLM Development & NLP (Core)
• Design and fine-tune LLMs for Arabic language tasks
• Text generation, classification, summarization
• Arabic grammar correction, dialect handling
• Build and optimize RAG pipelines
• Develop prompt engineering strategies for Arabic + English contexts
2. Data & Arabic Language Engineering
• Build and curate Arabic datasets
• Handle:
• Dialects (Gulf, MSA, etc.)
• Data cleaning, normalization
• Define evaluation benchmarks for Arabic LLM quality
3. AI System Architecture
• Develop LLM-powered systems using:
• LangChain / LangGraph / Llama / OpenAI APIs
• Vector databases (ChromaDB, FAISS, etc.)
• Integrate LLMs into:
• APIs
• Enterprise systems
• AI agents / copilots
4. Production & MLOps
• Deploy scalable AI systems using:
• Docker, Kubernetes
• Cloud platforms (Azure, AWS, GCP)
• Optimize:
• Latency
• Cost
• Throughput
5. Cross-functional Collaboration
• Work with:
• PMs (scope, delivery, timelines)
• BAs (requirements translation → AI logic)
• QA (model validation & test cases)
• Support client demos and AI solution design
6. Governance Alignment (Critical for Nabeh)
• Ensure:
• AI outputs align with client expectations
• Traceability (data → model → output)
• Support:
• BRD validation (AI feasibility)
• UAT and acceptance criteriaRequirements
Required Skills
Technical
• Strong in:
• Python (PyTorch / TensorFlow)
• NLP & LLMs (Transformers, RAG)
• Experience with:
• LangChain / LLM frameworks
• Vector databases
• Prompt engineering
Arabic AI (Mandatory)
• Native or fluent Arabic
• Experience in:
• Arabic NLP
• Dataset preparation for Arabic
• Handling dialects
Engineering & Deployment
• APIs (FastAPI / Flask)
• Microservices architecture
• Docker, Kubernetes
• CI/CD pipelines
Language Requirements
• Arabic: Native / Fluent (MANDATORY)
• English: Professional (MANDATORY)
Preferred Qualifications
• MSc or higher in AI / Data Science / NLP
• Experience in:
• Arabic LLMs (high priority)
• Government or enterprise AI projects
• Certifications:
• Azure AI / ML
• MLOps / Cloud certifications
Requirements
- •Strong Python (PyTorch / TensorFlow) skills
- •Proficiency in NLP and LLMs (Transformers, RAG)
- •Experience with LangChain / LLM frameworks
- •Experience with Vector databases
- •Experience with Prompt engineering
- •Native or fluent Arabic speaker
- •Experience in Arabic NLP
- •Experience in Arabic dataset preparation
Nice to Have
- •MSc or higher in AI / Data Science / NLP
- •Experience in Arabic LLMs
- •Experience in Government or enterprise AI projects
- •Azure AI / ML certifications
- •MLOps / Cloud certifications
Responsibilities
- •Design and fine-tune LLMs for Arabic language tasks
- •Build and optimize RAG pipelines
- •Develop prompt engineering strategies
- •Build and curate Arabic datasets
- •Define evaluation benchmarks for Arabic LLM quality
- •Develop LLM-powered systems
- •Deploy scalable AI systems
- •Optimize Latency, Cost, Throughput
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60 seconds. $3.99 one-time.
Master-Works is a Saudi Arabian company involved in construction and supplying building materials. They serve clients within the Kingdom.
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