Machine Learning Engineer 2026

Numrah is seeking a Machine Learning Engineer to design and implement ML solutions from ideation to production. The role involves fine-tuning and integrating LLMs, deploying and monitoring LLM-powered features at scale, and collaborating with engineering and product teams. The ideal candidate will write clean, scalable code, create detailed technical documentation, and stay current with the latest ML research, LLM capabilities, and MLOps best practices.

Must Have

• Be an Arabic speaker
• Have at least 1-2 year of non-internship experience in Machine Learning
• Strong ML and DL theory background
• Production experience training and fine-tuning LLMs, with practical knowledge of transformer architectures in NLP applications
• Experience with MLOps best practices
• Collaborative mindset and ability to communicate technical ideas clearly

Good to Have

• Experience deploying LLM-based features to production
• Knowledge 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

At Numrah, we build intelligent, modern applications that combine cutting-edge engineering with practical machine learning. We're looking for a Machine Learning Engineer who is deeply grounded in ML theory and excited to Design and implement ML solutions from ideation to production Fine-tune and integrate LLMs Deploy and monitor LLM-powered features at scale in real-world products Collaborate with engineers and product teams to build intelligent, user-facing features Write clean, scalable code and detailed technical documentation Stay current with the latest in ML research, LLM capabilities, and MLOps best practices

What You’ll Do

• Design and implement ML solutions from ideation to production
• Fine-tune and integrate LLMs
• Deploy and monitor LLM-powered features at scale in real-world products
• Collaborate with engineers and product teams to build intelligent, user-facing features
• Write clean, scalable code and detailed technical documentation
• Stay current with the latest in ML research, LLM capabilities, and MLOps best practices

Must-Haves

1. Be an Arabic speaker

2. Have at least 1-2 year of non-internship experience in Machine Learning

3. Strong ML and DL theory background, you don't just use things, you know how they are working under the hood.

4. Production experience training and fine-tuning LLMs, with practical knowledge of transformer architectures in NLP applications.

5. Experience with MLOps best practices.

6. Collaborative mindset and ability to communicate technical ideas clearly

Nice-to-Have

• Experience deploying LLM-based features to production
• Knowledge 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