Design and implement ML solutions, fine-tune and integrate LLMs, and collaborate on deploying intelligent features in production environments.
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, 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 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
- Be an Arabic speaker
- Have 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 architectures
- Solid production-level Python experience and strong software engineering fundamentals (OOP, OOD, DSA)
- Familiarity with LLM integration frameworks like HuggingFace Transformers, OpenAI, or LangChain
- Familiarity with ML data pipelines and manipulation tools (e.g., Pandas, NumPy)
- Strong research, writing, and documentation skills
- Collaborative mindset and ability to communicate technical ideas clearly
Nice-to-Haves
- 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
Top Skills
AWS
Azure
Docker
GCP
Huggingface Transformers
Langchain
Numpy
Openai
Pandas
Python
Similar Jobs
Information Technology • Mobile • News + Entertainment • Social Media
As a Machine Learning Engineer, you'll design and deploy ML models to optimize ads through ad ranking, bidding, and measurement, while managing the complete ML lifecycle.
Top Skills:
KafkaPythonPyTorchScalaSparkTensorFlow
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Lead innovation in predictive modeling, design ML solutions, collaborate with stakeholders, and enhance value measurement systems to drive Block's growth.
Top Skills:
Deep LearningMachine LearningXgboost
.png)
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
As a Staff Machine Learning Engineer, you will define technical strategies, design ML models for risk assessment, and build scalable ML systems.
Top Skills:
DnnsGenaiLlmsMachine LearningTransformers
What you need to know about the Sydney Tech Scene
From opera to comedy shows, the Sydney Opera House hosts more than 1,600 performances a year, yet its entertainment sector isn't the only one taking center stage. The city's tech sector has earned a reputation as one of the fastest-growing in the region. More specifically, its IT sector stands out as the country's third-largest, growing at twice the rate of overall employment in the past decade as businesses continue to digitize their operations to stay competitive.
