Expert AI and Language Model Consultant

AI Expert and Consultant Job Overview

We are seeking a seasoned AI professional to provide technical expertise for our Large Language Model (LLM) project. As a key advisor, you will oversee the development of Arabic LLM initiatives, ensuring strategic guidance and technical oversight.

• Provide strategic guidance and technical oversight for the development of Arabic LLM initiatives
• Evaluate and select appropriate base models based on benchmarking performance for Arabic language tasks
• Design data acquisition strategies and processing pipelines for Arabic language data, including Omani dialect-specific data
• Lead continuous pre-training, supervised fine-tuning, RLHF and DPO implementation processes
• Design and implement comprehensive evaluation frameworks for LLM assessment across diverse Arabic tasks
• Establish benchmarking methodologies aligned with international standards
• Coordinate model submissions to relevant leaderboards to demonstrate comparative performance
• Architect efficient tokenization approaches optimized for Arabic language to improve token fertility
• Develop RAG frameworks for government document search and integration
• Consult on model optimization techniques for efficient inference, including quantization strategies and knowledge distillation
• Implement model compression techniques to create efficient student models for deployment
• Lead the design of model guardrails that align with Omani cultural values and governmental requirements
• Advise on infrastructure requirements for model training, fine-tuning, and deployment
• Collaborate with vendor teams to implement the technical solution
• Conduct knowledge transfer sessions to build local AI capabilities
• Guide the development of metrics and monitoring frameworks for model performance
• Implement and manage data annotation pipelines and quality assurance processes

• Degree(s) in Computer Science, AI, Machine Learning, or a related field
• 5+ years of experience in LLM and deep learning, with specific expertise in transformer-based language models
• Hands-on experience with full-cycle LLM development, including pre-training, fine-tuning, and deployment
• Demonstrated expertise in Arabic NLP, particularly tokenization approaches and language-specific optimization
• Extensive experience with LLM evaluation methodologies, including automatic metrics and human evaluation protocols
• Proficiency in designing, implementing, and analyzing benchmark suites for language models
• Experience with leaderboard submission processes and performance verification
• Experience with RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Preference Optimization) techniques
• Strong knowledge of model quantization techniques (INT8, INT4, GPTQ, AWQ, etc.) and their impact on model performance
• Deep expertise in knowledge distillation methods for creating smaller, efficient student models from larger teacher models
• Practical knowledge of efficient model inference strategies and optimization techniques
• Deep understanding of RAG systems and information retrieval
• Proficiency in PyTorch, TensorFlow, or JAX for LLM development
• Strong understanding of distributed training systems and GPU optimization
• Experience with containerization (Docker) and orchestration (Kubernetes) for ML workloads
• Knowledge of responsible AI practices and guardrail implementation
• Experience working with government or enterprise LLM deployments
• Proficiency with Scale AI SGP (Synthetic Generation Platform) or similar tools for data generation and model evaluation
• Experience with data annotation platforms and human feedback collection systems
• Leadership skills with ability to guide technical teams and communicate with stakeholders

• Previous experience with Arabic-specific language models like Jais or similar
• Experience with AWS cloud services, particularly SageMaker, HyperPod, Trainium, and other AI/ML infrastructure
• Previous work with model customization and adaptation for specific languages or domains
• Understanding of data privacy considerations for government applications
• Experience implementing token efficiency strategies for non-English languages
• Knowledge of MLOps practices for LLM lifecycle management
• Experience with post-training optimization techniques like pruning, weight sharing, and structured sparsity
• Demonstrated ability to communicate complex technical concepts to non-technical stakeholders
• Experience with Scale AI's Human Feedback and AI Evaluation tools
• Familiarity with other data annotation and synthetic data generation platforms (Snorkel, Humanloop, etc.)
• Demonstrated success in optimizing models for resource-constrained environments
• Experience with holistic LLM valuation methodologies that assess both performance and business impact
• Familiarity with public LLM benchmarks and Arabic-specific evaluation suites
• Experience benchmarking models against commercial offerings (OpenAI, Claude, etc.)

A competitive compensation package and opportunities for growth and professional development in a dynamic environment.

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