Machine Learning Engineer

Job description Discover the Opportunity

We’re partnering with a leading financial services organisation in Abu Dhabi that is continuing to expand its AI and Machine Learning capabilities.

They’re looking for a highly technical, hands‑on Machine Learning Engineer to build and deploy scalable AI systems that solve complex, real‑world business problems.

This role is heavily focused on production engineering. You’ll work across the full ML lifecycle, from model development and training through to deployment, optimisation and integration into live applications.

• Design, train and deploy production‑grade Machine Learning and AI models across a range of complex use cases.
• Build end‑to‑end ML pipelines covering data ingestion, transformation, training, validation, deployment and ongoing optimisation.
• Work with traditional ML, deep learning, neural networks and emerging Agentic AI architectures.
• Fine‑tune LLMs/SLMs and contribute to the development of more complex Generative AI solutions.
• Automate model training, testing and deployment through CI/CD and modern MLOps practices.
• Build scalable model serving capabilities for both real‑time and batch inference.
• Work closely with Software, Data and AI teams to integrate models into production applications.

• 3–7 years of experience building and deploying production‑grade, scalable AI/ML systems.
• Strong hands‑on expertise across Machine Learning, with experience in areas such as deep learning, NLP, Computer Vision or Generative AI.
• Strong understanding of ML system architecture and taking models from development through to production.
• Experience with LLMs, model fine‑tuning and modern AI architectures.
• Experience with model serving and API development using technologies such as FastAPI or Flask.
• Understanding of Docker, Kubernetes, CI/CD and MLOps tooling such as MLflow or Kubeflow.
• Experience deploying Machine Learning models across AWS or Azure.
• Bachelor’s degree in Computer Science, Engineering or a related technical discipline;
  Master’s or PhD would be advantageous.