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Job Description
We're looking for a Machine Learning Engineer who is deeply grounded in ML theory and excited to design, train, fine-tune, and deploy Large Language Models (LLMs) and other ML systems in real-world production environments.You’ll work closely with backend and product individuals/teams to deliver smart, scalable features—from rapid experimentation to full-scale deployment. If you’re passionate about ML theory, hands-on with LLMs, and know how to ship high-impact AI features, this role is for you.What You’ll DoDesign and implement ML solutions from ideation to productionFine-tune and integrate LLMsDeploy and monitor LLM-powered features at scale in real-world productsCollaborate with engineers and product teams to build intelligent, user-facing featuresWrite clean, scalable code and detailed technical documentationStay current with the latest in ML research, LLM capabilities, and MLOps best practicesMust-HavesBe an Arabic speakerHave at least 1 year of non-internship experience in Machine Learning.Strong ML and DL theory background, you don't just use things, you know how they are working under the hood.Experience training and fine-tuning LLMs, with practical knowledge of transformer architecturesSolid production-level Python experience and strong software engineering fundamentals (OOP, OOD, DSA)Familiarity with LLM integration frameworks like HuggingFace Transformers, OpenAI, or LangChainFamiliarity with ML data pipelines and manipulation tools (e.g., Pandas, NumPy)Strong research, writing, and documentation skillsCollaborative mindset and ability to communicate technical ideas clearlyNice-to-HavesExperience deploying LLM-based features to productionKnowledge of parameter-efficient fine-tuning (LoRA, QLoRA, PEFT)Familiarity with RAG pipelines and vector databases (e.g., Pinecone, Weaviate)Understanding of model serving and inference optimization (quantization, batching)Exposure to MLOps practices (monitoring, versioning, CI/CD for ML)Experience with RESTful APIs, Docker, and cloud platforms (GCP, AWS, or Azure)Interest in NLP applications, smart assistants, or chatbot systems
