LLM Engineer

About Our ClientOur client is a rapidly growing AI technology company headquartered in Abu Dhabi, specializing in Enterprise AI, Generative AI, and Large Language Model (LLM) solutions.Working closely with government organizations and leading enterprises across the Middle East, the company develops secure, scalable, and sovereign AI capabilities, with a strong emphasis on multilingual and Arabic-language AI applications.ResponsibilitiesDesign and execute LLM fine-tuning and post-training workflows using SFT, LoRA, QLoRA, DPO, and RLHFBuild and improve high-quality training datasets, including data preparation, annotation standards, synthetic data generation, and quality assuranceDevelop robust model evaluation frameworks using automated benchmarks and human-in-the-loop assessment methodsEnhance model performance through distributed training, quantization, and inference optimizationDeploy customized LLM solutions in private-cloud, on-premise, and security-sensitive environmentsPartner with product, solutions, and engineering teams to deliver enterprise AI use casesEvaluate emerging foundation models and recommend optimal architectures for business requirementsContribute to MLOps best practices, experiment tracking, and reproducible training pipelinesRequirementsBachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field3+ years of Machine Learning Engineering experience with hands-on exposure to LLM training, fine-tuning, or model optimizationStrong proficiency in Python, PyTorch, and the Hugging Face ecosystemPractical experience with LoRA, QLoRA, PEFT, DPO, RLHF, ORPO, or similar techniquesSolid understanding of Transformer architectures, tokenization, context management, and LLM inferenceExperience training models on multi-GPU infrastructure using frameworks such as DeepSpeed or FSDPStrong analytical skills with experience measuring and improving model qualityExcellent communication skills in English