✨ AI Summary
This role is for a Senior Machine Learning Engineer to join an Innovation Hub/AI Lab backed by a large bank in Abu Dhabi. The position requires 3-7 years of experience in building production-grade, scalable AI/ML systems with a strong emphasis on Python and ML engineering capabilities. The candidate should have expertise in areas like supervised/unsupervised ML, deep learning, NLP, Computer Vision, and/or GenAI/LLMs, and be proficient in building end-to-end ML pipelines, production model serving using FastAPI/Flask, and understanding ML system architecture. Experience with real-time/batch inference, model optimization, Docker, Kubernetes, CI/CD, MLflow/Kubeflow, and deployment on AWS or Azure is also essential. Experience with training/deploying traditional ML, neural networks, and Agentic AI models is required, with a preference for experience in fine-tuning SLMs/LLMs and building complex AI architectures.
Requirements
The ideal candidate is a production-focused Machine Learning Engineer with 3-7 years of experience in building scalable, production-grade AI/ML systems. Key requirements include strong Python and ML engineering skills, experience with various ML techniques (supervised/unsupervised, deep learning, NLP, Computer Vision, GenAI/LLMs), building end-to-end ML pipelines, production model serving, ML system architecture understanding, and knowledge of CI/CD, Docker, Kubernetes, and ML lifecycle management tools like MLflow or Kubeflow, with deployment experience on AWS or Azure.
Description
**RECRUITING**Contract OR PERM Open to relocators Job Title – Machine Learning EngineerSalary – N/AJob Type - Contract Or Perm Location – Abu DhabiStart Date – ASAPWe are working on a brand-new project, which is an Innovation Hub/Ai Lab backed by a large bank in the region.The candidate my client want is essentially a production-focused Machine Learning Engineer with 3–7 years experience, rather than a pure Data Scientist. The major requirements I would source against are:3–7 years experience building production-grade, scalable AI/ML systems.Very strong Python + ML engineering capability.Experience with supervised/unsupervised ML, deep learning, NLP, Computer Vision and/or GenAI/LLMs — you don't necessarily need every area but should have genuine depth.Building end-to-end ML pipelines: ingestion → transformation → training → validation → deployment.Production model serving and APIs using FastAPI / Flask.Strong ML system architecture understanding.Experience with real-time and/or batch inference and model performance optimisation.Knowledge of Docker, Kubernetes and CI/CD.Exposure to MLflow and/or Kubeflow for lifecycle management.Deployment onto AWS or Azure.Experience training/deploying traditional ML, neural networks and Agentic AI models.Ideally experience fine-tuning SLMs/LLMs and building more complex AI architectures.Thanks,Ollie