About the RoleWe're looking for an AI/ML Engineer to join our Insights & Personalization pod within TymeX, a team building the intelligence layer that makes digital banking adaptive, transparent, and deeply personalized. This role is perfect for someone who understands that production ML in financial services isn't just about model accuracy; it's about building trustworthy, explainable systems that customers can rely on with their money.You'll design and deploy machine learning systems across the full stack, from transaction intelligence and behavioral pattern recognition to predictive forecasting, conversational AI, and agentic solutions. You'll be building production systems that customers interact with directly, making the impact of your work tangible and immediate. As part of the Tyme Group operating across multiple markets, you'll build systems that create compounding value as they learn from more data and usage, with the opportunity to see your work scale globally across our digital banking platforms.What You'll DoAs an AI/ML Engineer, you'll work across the full ML lifecycle, from model design and experimentation to large-scale deployment and performance optimization, within a distributed, microservices-based, and cloud-native environment.You will:Design, build, and optimize AI/ML pipelines for real-time and batch inference, leveraging modern MLOps practices.Collaborate with data engineers and software developers to integrate models into TymeX's banking platform, ensuring reliability, monitoring, and version control.Research, prototype, and productionize models in areas such as credit scoring, fraud detection, transaction classification, personalization, and conversational AI.Implement robust model evaluation, A/B testing, and drift detection frameworks to ensure accuracy and stability over time.Contribute to internal frameworks and libraries to standardize ML development workflows across teams.Explore and evaluate emerging techniques in LLMs, Generative AI, and reinforcement learning applicable to TymeX's ecosystem.Mentor junior engineers and collaborate closely with product and infrastructure teams to ensure model readiness for global scale.