We are seeking skilled AI/ML Engineers to design, build, and deploy intelligent data-driven solutions across key financial domains including Payments, Investor Services & Trade, Pricing & Billing, and Liquidity Management . The role focuses on leveraging advanced machine learning techniques to optimise processes, enhance decision-making, and deliver scalable, production-grade analytics solutions. Experience Levels Mid-Level AI/ML Engineer: 4–7 years of relevant experience Senior AI/ML Engineer: 7+ years of relevant experience Key Responsibilities Design, develop, and deploy machine learning models and AI solutions aligned to business use cases. Work across financial domains including Payments, Trade & Investor Services, Pricing & Billing, and Liquidity Management. Build and maintain scalable data pipelines and feature engineering workflows. Translate complex business problems into analytical and ML solutions. Collaborate with data engineers, analysts, and business stakeholders to deliver end-to-end solutions. Ensure model performance, monitoring, and continuous improvement in production environments. Apply best practices in MLOps, model governance, and data quality. Support real-time and batch processing use cases where applicable. Senior Level Additional Responsibilities: Lead solution design and architecture for AI/ML initiatives. Mentor junior team members and provide technical guidance. Drive strategic AI adoption across business domains. Engage with senior stakeholders and influence decision-making. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Engineering, or related field. Technical Skills Strong programming skills in Python (mandatory). Experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Proficiency in SQL and working with large datasets. Experience with cloud platforms (AWS, Azure, or GCP). Knowledge of data engineering concepts (ETL pipelines, data lakes, streaming). Familiarity with MLOps tools (e.g., MLflow, Docker, Kubernetes, CI/CD pipelines). Experience with data visualisation tools (e.g., Power BI, Tableau). Domain Experience (Highly Preferred) Pricing & Billing: Dynamic pricing models, revenue optimisation, billing analytics. Liquidity Management: Cash flow forecasting, liquidity risk modelling, treasury analytics. Core Competencies Strong analytical and problem-solving skills. Ability to work with complex financial datasets. Excellent communication and stakeholder engagement skills. Attention to detail and commitment to data quality. Ability to manage multiple priorities in a fast-paced environment. #J-18808-Ljbffr