Numrah is hiring a Machine Learning Engineer 2026

We develop sophisticated, innovative applications integrating advanced engineering with pragmatic machine learning approaches. We seek a Machine Learning Engineer deeply rooted in ML theoretical foundations and passionate about Creating and executing ML solutions from conceptualization through implementation Fine-tune and integrate Large Language Models Deploy and manage LLM-driven features comprehensively in real-world environments Collaborate with engineering and product teams to construct intelligent, user-centric features Generate pristine, extensible code and comprehensive technical documentation Remain updated on contemporary ML research, LLM capabilities, and MLOps industry standards What You'll Accomplish - Conceptualize and execute ML solutions from initial idea to production implementation - Refine and integrate Large Language Models - Launch and supervise LLM-powered features at enterprise scale within practical products - Engage with engineering and product groups to develop intelligent, user-interaction features - Construct clean, scalable programming and meticulous technical documentation - Continuously track emerging ML research, LLM capabilities, and MLOps methodological practices Essential Qualifications 1. Native Arabic language proficiency 2. Minimum 1-2 years professional (non-internship) Machine Learning experience 3. Robust Machine Learning and Deep Learning theoretical understanding, demonstrating comprehensive comprehension of underlying mechanisms 4. Practical production experience training and customizing Large Language Models, with substantial transformer architecture knowledge in Natural Language Processing applications 5. Proven MLOps best practice expertise 6. Collaborative disposition with exceptional technical communication capabilities Preferred Complementary Skills - Experience deploying Large Language Model-based features in production environments - Understanding parameter-efficient fine-tuning methodologies - Familiarity with retrieval-augmented generation pipelines and vector database technologies - Comprehension of model serving and inference optimization techniques - MLOps practice exposure - Experience with RESTful API architectures, containerization technologies, and cloud platform ecosystems - Enthusiastic about Natural Language Processing applications, intelligent assistants, and conversational system development