Machine Learning Engineer – EMEA

We are hiring a Machine Learning Engineer / Applied Scientist to develop and improve LLM-driven solutions across operational and automation workflows. The role will focus on fine-tuning models, building evaluation frameworks, and improving model accuracy for domain-specific use cases. You will work closely with engineering teams to integrate ML improvements into production environments and reduce hallucinations through grounded AI systems. This role is ideal for a hands-on ML professional who can own model quality, experimentation, and continuous improvement.About usNOK Human Capital is a leading HR consulting and talent acquisition firm with a global footprint and a proven track record of supporting Fortune 500 clients. We specialize in connecting top-tier talent with industry leaders, driving innovation, and fostering high-performance cultures across the MENA region and beyond.Key ResponsibilitiesFine-tune and optimize Large Language Models for domain-specific tasks such as estimation, planning, and automation.Design and implement evaluation frameworks using automated metrics, human evaluation, and model-based assessment.Build and maintain RAG pipelines that ground model outputs in codebase, documentation, and operational data.Develop prompt engineering strategies and optimize prompt chains for multi-step AI workflows.Collaborate with software engineering teams to integrate model improvements into production services.Analyze model failure modes, identify accuracy gaps, and recommend targeted improvements.Establish baseline metrics, dashboards, and reporting to track model accuracy over time.Stay updated on LLM advancements and recommend relevant techniques for adoption.RequirementsMS or PhD in Computer Science, Machine Learning, NLP, Statistics, or a related quantitative field, or equivalent industry experience.3+ years of hands-on experience with deep learning, NLP, and LLM techniques.2+ years of experience fine-tuning language models.2+ years of experience building end-to-end ML pipelines, including data preparation, training, evaluation, and deployment.Strong Python skills with experience in deep learning and transformer-based frameworks.Experience with model evaluation methodologies and metrics such as BLEU, ROUGE, accuracy, F1, and human evaluation.Hands-on experience with RAG architectures, vector databases, embedding models, and prompt engineering.Ability to work independently and deliver results with minimal supervision.