ML Ops Engineer

MLOps Engineer

Location: Abu Dhabi,Khalifa City UAE | Onsite | Contract

Key Responsibilities

• Develop, deploy and maintain machine learning models and data-driven solutions.
• Work with large and complex datasets to support AI and machine learning use cases.
• Perform data preprocessing, feature engineering and model evaluation.
• Build and maintain scalable ML pipelines and deployment workflows.
• Support MLOps and LLMOps architecture, automation and model lifecycle management.
• Collaborate with Data Scientists, Data Engineers and Software Engineers to productionise ML models.
• Implement CI/CD practices for machine learning workflows.
• Monitor model performance, reliability and production environments.
• Support containerised ML workloads using Docker and cloud technologies.
• Contribute to technical documentation, development standards and best practices.

Required Experience

• 3–7+ years of experience in Data Science, Machine Learning or MLOps.
• Proven experience developing and deploying machine learning models into production.
• Strong knowledge of machine learning techniques including NLP, Deep Learning and Computer Vision .
• Strong programming skills in Python, SQL and Spark .
• Hands-on experience with ML frameworks and tools such as TensorFlow, PyTorch, Spark MLlib, MLflow, LangChain or LlamaIndex .
• Strong understanding of MLOps and LLMOps architectures .
• Experience working with large, complex datasets.
• Experience with Docker and cloud-based development environments.
• Familiarity with Databricks and Microsoft Azure .
• Experience with Azure DevOps and CI/CD practices.

Technical Stack

Languages: Python, SQL, Spark

ML/AI: TensorFlow, PyTorch, Spark MLlib, MLflow, NLP, Deep Learning, Computer Vision, LangChain, LlamaIndex

Cloud & Data: Microsoft Azure, Databricks

DevOps: Azure DevOps, Docker, CI/CD.