Machine Learning Engineer

Role Overview

This position is based on-site in Abu Dhabi and requires relocation. The role involves designing and developing scalable machine learning models alongside AI-powered solutions aimed at solving intricate business challenges and improving decision-making workflows.

Key Responsibilities

• Analyze and work with large complex data sets to tackle difficult business problems.
• Efficiently train and deploy standard machine learning models, neural networks, and agentic AI models.
• Create, train, and enhance machine learning models using cutting-edge algorithms and frameworks.
• Develop robust production-grade ML pipelines covering data ingestion, transformation, training, validation, and deployment.
• Automate model training, testing, and deployment pipelines employing CI/CD and MLOps methodologies.
• Collaborate closely with multidisciplinary teams to embed models within applications to provide holistic solutions.
• Fine-tune supervised language models and large language models, and design complex AI system architectures.

Required Experience and Qualifications

• Between 3 to 7 years of experience building scalable, production-ready AI systems.
• Expertise in supervised and unsupervised learning, deep learning, natural language processing, computer vision, and generative AI including large language models.
• Strong skills in machine learning system design and architecture.
• Knowledge of model serving, API development (e.g., FastAPI, Flask), optimizing models for real-time and batch inference.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes, plus CI/CD pipelines and MLOps tools like MLflow or Kubeflow.
• Proficiency deploying models on cloud platforms such as AWS or Azure.
• Minimum education: Bachelor’s degree in Computer Science, Engineering, or related discipline.
• Preferred advanced degrees: Master’s or PhD in Computer Science or related fields.