AI/LLM Engineer

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. 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.

Desired Candidate Profile

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.