CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and
Key Responsibilities Design, develop, and optimize classical machine learning models (e.g., regression, classification, clustering, time-series forecasting, anomaly detection) Build and deploy deep learning models using frameworks such as TensorFlow or PyTorch for structured, unstructured, and multimodal data Fine-tune and
Role Overview The Senior Elastic Engineer leads the design, optimization, and strategic evolution of Elastic environments that support advanced security and observability use cases. This role combines deep hands-on engineering with architectural leadership, with responsibility for scalability, resilience,
Key Responsibilities Lead the development and deployment of advanced data science and AI solutions across Machine Learning (ML), Deep Learning (DL), Generative AI, and Agentic AI use cases Lead the end-to-end model lifecycle management, including data ingestion, feature engineering,
Key Responsibilities Define and drive enterprise-level architecture for Data Science, AI/ML, Generative AI, and Agentic AI solutions, ensuring alignment with organizational strategy and technology roadmaps Lead the design of scalable, secure, and high-performance AI platforms, covering