AI/LLM Engineer (Saudi Arabia)

This position is for building, deploying and evaluating Client's Arabic AI tutor for mathematics and computer science: preparing Arabic training data, fine-tuning, aligning and evaluating LLMs on Shaheen III and Ibex, and integrating the tutor into the learning platform for a pilot in at least 10 Saudi schools. The position is part of the RDIA-funded project 5870, “An AI-Powered Arabic Tutoring Platform for STEM Education in the Kingdom.” Two engineers will be hired into this role. Key Responsibilities • Prepare Arabic training datasets from educational materials and consented platform interactions. • Fine-tune, align, and evaluate commercial and open-source LLMs using Shaheen III and Ibex computing platforms. • Develop Arabic STEM benchmarks, preference-training methods, and student-safety guardrails. • Integrate AI tutoring capabilities into the learning platform, including Arabic right-to-left interfaces. • Deploy and optimize models for reliable, low-latency real-time interactions. • Support school pilot implementation, evaluation, and teacher feedback collection. • Ensure student data privacy and compliance with Saudi data protection requirements. • Contribute to research publications, technical reports, and project deliverables. Qualifications & Experience • MSc in Computer Science, Artificial Intelligence, or a related field; alternatively, a BSc with at least one year of relevant experience. • Hands-on experience in LLM fine-tuning, evaluation, and AI application deployment. • Professional proficiency in Arabic and English. • Experience with RLHF/DPO, educational technology, or mathematics/programming education is preferred. Technical Skills • Advanced Python and PyTorch. • Hugging Face Transformers, PEFT, and TRL. • Distributed GPU training using DeepSpeed or FSDP. • LLM evaluation, reward modeling, and preference optimization. • Arabic NLP, data pipelines, and OCR. • Model serving and inference optimization using tools such as vLLM. • APIs, Docker, Git, CI/CD, and production deployment.