AI Expert and Consultant

About the Role

We are seeking an experienced AI Expert and Consultant to join our National Large Language Model (LLM) Project, replacing ChatGPT usage in the workplace. As a key technical advisor, you will provide expertise across the full LLM stack, from model training and fine-tuning to deployment and RAG implementation.

Key Responsibilities:

  • Provide strategic guidance and technical oversight for the development of Arabic LLM initiative
  • Evaluate and select appropriate base models (7B and 30B parameter 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 (Retrieval Augmented Generation) 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 AWS/Cohere/other 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

Requirements:

  • 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

Preferred Qualifications:

  • 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.)
  • Experience building custom evaluation harnesses for LLM performance assessment
  • 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.)
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