Requirements
Candidates should have 3-7 years of experience building production-grade, scalable AI/ML systems, with strong expertise in areas like deep learning, NLP, computer vision, or generative AI/LLMs. Proficiency in ML system architecture, productionization, model serving with tools like FastAPI/Flask, and experience with Docker, Kubernetes, CI/CD, and MLOps tools such as MLflow or Kubeflow are essential. Experience deploying models on AWS or Azure, and a strong understanding of model performance optimization and inference are also required. A Bachelor's degree in Computer Science, Engineering, or a related field is mandatory.
Description
Machine Learning EngineerContract - 3-6 monthsOnsite - Abu DhabiWe are looking for a Machine Learning Engineer to design, develop, and deploy scalable machine learning and AI solutions that solve complex business challenges and support smarter decision-making.What You'll Be DoingWork with large and complex datasets to solve challenging business problems.Design, develop, train, and optimise machine learning models using modern algorithms and frameworks.Build and maintain production-grade, end-to-end ML pipelines covering data ingestion, transformation, training, validation, and deployment.Train and deploy standard ML, neural network, and agentic models efficiently.Automate model training, testing, and deployment through CI/CD pipelines and MLOps practices.Fine-tune SLMs and LLMs and develop complex AI architectures.Develop solutions across areas such as supervised and unsupervised learning, deep learning, NLP, computer vision, and generative AI.Collaborate with engineering, product, data, and other cross-functional teams to integrate AI models into applications and deliver end-to-end solutions.Design scalable ML system architectures and optimise models for real-time and batch inference.What We're Looking For3–7 years experience building production-grade, scalable AI/ML systems.Strong expertise in machine learning, with experience across areas such as deep learning, NLP, computer vision, or generative AI/LLMs.Strong understanding of ML system architecture and productionisation.Experience with model serving and API development using tools such as FastAPI or Flask.Good understanding of Docker, Kubernetes, CI/CD, and MLOps tools such as MLflow or Kubeflow.Experience deploying machine learning models on AWS or Azure.Strong understanding of model performance optimisation and inference.Bachelor's degree in Computer Science, Engineering, or a related field.Nice to HaveMaster's or PhD in Computer Science, Engineering, AI, or a related discipline.Hands-on experience with agentic AI systems and advanced LLM architectures.Experience designing and operating large-scale AI platforms in production.The OpportunityThis is a great opportunity for an experienced Machine Learning Engineer to work on production-scale AI systems, from model development and experimentation through to deployment, automation, and continuous optimisation.